Structure and Governance in Industrial Districts:
Implications for Competitive Advantage
joms_951772..803Andaç T. Arıkan and Melissa A. Schilling
Florida Atlantic University; Stern School of Business, New York Universityabstract The existing research on industrial districts is fragmented, and yields conflicting advice for managers about the benefits and costs of locating in an industrial district. We resolve much of this ambiguity by synthesizing and integrating the existing research, and developing a typology of districts based on the continuous dimensions of need for coordination and
centralization of control. In so doing, we elucidate why different types of industrial districts have
different structures, and different competitive implications. We introduce four archetypes of industrial districts (based on extreme values of our two dimensions), and for each we discuss the benefits and costs of locating in the district, the sources of competitive advantage for members of the district vis-à-vis non-members, and the sources of competitive advantage a district firm may gain over other members of the same district.
INTRODUCTION
Industrial districts[1] defined as geographical agglomerations of firms that belong to the same or related industries (Porter, 1998b), have become an important part of the competitive landscape (Ellison and Glaeser, 1997; Porter, 1990, 1998a; Rosenfeld, 1996). Studies of industrial districts date back to Marshall (1920), but they proliferated in the last three decades (see Storper, 1997, and McCann and Folta, 2008, for reviews). While early research was done predominantly by regional development scholars and economic geographers, strategy scholars have recently become interested in districts, and in line with the fundamental question of their field, started examining whether firms in a district have a competitive advantage over those that are not. Surprisingly, studies revealed conflicting findings on the effect of locating in districts with some finding positive effects (Baptista and Swann, 1998; Bell, 2005; Decarolis and Deeds, 1999; Molina-Morales and Martinez-Fernandez, 2003), and others negative effects (Appold, 1995; Glasmeier, 1991; Shaver and Flyer, 2000; Staber, 1998; Stuart and Sorenson, 2003). A quick review of the theories that are brought to bear on industrial districts to explain such discrepancies reveals a multiplicity of theoretical approaches including
Address for reprints: Andaç T. Arıkan, Florida Atlantic University, College of Business, Department of
Management Programs, 777 Glades Road, Boca Raton, FL 33431, USA (aarikan@fau.edu). © 2010 The Authors
pecuniary and knowledge externalities (Marshall, 1920), regional resource endowments (Enright, 1991), transaction cost economics (Scott, 1988), embeddedness (Piore and Sabel, 1984), localized learning (Maskell and Malmberg, 1999), and knowledge creation (Arikan, 2009), along with numerous different terms used by different researchers to represent the form and characteristics of local firm concentrations.[2] The theoretical fragmentation in the field has got to a point to even lead some researchers to question the very utility of the district concept (Martin and Sunley, 2003).
The state of the literature as summarized above is troublesome for both scholars and managers. We still, for example, do not know when firms will choose to locate in districts, whether they will have a competitive advantage over those that do not, or what the sources of competitive advantage are for firms located in a district against other district firms. In an effort to provide clearer answers to these questions, we take as our starting point the idea that districts are not homogenous but rather vary significantly in terms of why and how they emerge, how they are governed, and consequently what types of costs and benefits they create for firms located within them (Gordon and McCann, 2000; Markusen, 1996; McCann and Folta, 2009; Park, 1996; Storper and Harrison, 1991). Our contention is that a clearer understanding of the differences between districts is key in reducing theoretical confusion in the field and ambiguity around the competitive implications for firms of locating in districts. In an effort to offer a systematic under-standing of such differences, we proceed to develop a typology of districts with the ultimate purpose of exploring the competitive implications for district firms of such differences.
While developing our typology, we direct our attention to two continuous dimensions related to district governance: need for coordination, and centralization of control. Extreme values of these dimensions give rise to four archetypical districts. For each archetype, we first outline its characteristics. Second, we discuss the benefits and costs that accrue to firms in that archetype. Third, we examine the competitive implications of locating in the archetype, both in terms of district firms against non-district firms, and district firms against each other. We develop propositions regarding boundary conditions of competitive advantages district firms enjoy against non-district firms. Finally, we discuss how newcomers fare within each district. We address the issue of mixed types and longitudinal concerns in our discussion section.
Our contribution is threefold. First, we bring order and clarity to the theoretically fragmented field of district studies by bringing together numerous theoretical arguments made about districts in the context of a theoretically grounded, parsimonious typology. Second, we shed light into the sources of district-level and firm-level sources of competi-tive advantage in each archetypical district. Finally our propositions on boundary con-ditions of competitive advantage along with our discussion of costs associated with locating in each archetype illuminate the contingencies of competitive advantages within districts.
GOVERNANCE WITHIN INDUSTRIAL DISTRICTS
The variety of ways in which geographical agglomerations of firms in the same or related industries come into being and the types of governance we observe in them point to
important differences among districts (Gordon and McCann, 2000; Markusen, 1996). For example, districts vary from being almost purely market-like with no centralized control and characterized by governance only in the form of the invisible hand, to being very hierarchy-like with a single powerful entity exerting great control over others in the district. There are also districts that lie in an intermediate space on this continuum, where, for example, a well developed set of norms and/or trade associations can create a governing structure that facilitates significant coordination and cooperation among members. We contend that these different governance types lead to radically different types of interactions inside districts as well as different bases of competitive advantage for member firms. In this section, we describe the two continuous dimensions along which we argue districts vary in their structure and governance: need for coordination, and centralization of control.[3]
Need for Coordination
In many districts, firms are co-located but otherwise exhibit little coordination. Though cooperative behaviours might be observed, they are the outcome of market forces rather than through explicit control or negotiation between firms. In some industries, however, firms require more coordination than the market delivers. We argue that the primary factor that leads to a high need for coordination is a combination of complexity and imperfect separability.
Complexity. A complex industry environment often induces firms to exert more effort in coordinating their behaviours. Complexity may take many forms, but most relevant for our purposes are technological (i.e. knowledge-related) and demand complexity.
Many industries are characterized by high technological complexity in that the deliv-ery of the final product requires a large breadth of knowledge and a vast array of capabilities that are unlikely to be possessed by one firm. Prime examples include airplanes and computers. In such industries, the complex product system is often broken down into more manageable components, permitting firms to specialize on a narrower range of activities. In contrast, industries such as furniture and wine-making are char-acterized by relatively simpler technologies where individual firms may possess most or all of the knowledge and capabilities needed in production, and thus have little need for inter-firm coordination.
The second form of complexity relates to the nature of the environment. When an industry has many different types of customers with varying and rapidly-changing demand characteristics, the firms in that industry will experience pressure to produce more alternative configurations from available inputs and frequently change product characteristics in order to meet idiosyncratic customer preferences. If firms disaggregate the production activities across a group of participants, each can specialize in a narrow range of activities, yet through mixing and matching their components they can achieve greater flexibility and more closely meet heterogeneous demands (Schilling and Steensma, 2001). When interdependence between activities cannot be completely elimi-nated (as discussed below), this disaggregation will lead to more need for inter-firm coordination.
Imperfect separability. Whereas complexity provides the motivation for firms to pool their efforts to break down that complexity into more manageable pieces, it is the separability of activities that determines the ease or effectiveness of doing so (Baldwin and Clark, 1997; Schilling, 2000).
In one extreme, namely in product systems characterized by inseparability, compo-nents require such extensive interaction – and that interaction is so directly influenced by the design or nature of that component – that any change in the component requires extensive compensating changes in the other components of the system, or functionality is lost. For such systems, joint production within a single firm might be the most effective form of governance due to the difficulty of separating production activities in a way that permits multiple firms to act in parallel. In the steel industry, for example, the stages of production are highly interdependent and must be both geographically proximate and carefully synchronized. Steel manufacturers thus typically perform most or all of the stages of production in-house rather than disaggregating those stages across multiple firms.
In the opposite extreme, namely in product systems characterized by perfect separa-bility, the components (or processes involved in the production of those components) are highly independent – permitting either sequential stages or parallel activities to be performed by separate firms. If the activities in a production system are highly indepen-dent, they can be performed by different firms with little to no coordination. For example, the components of a plumbing system are highly standardized, permitting many firms to produce a chosen range of components without need for coordinating with producers of other components.
Many industries lie in between the above two extremes and are characterized by moderate levels of interdependence (i.e. imperfect separability), permitting activities to be performed by separate firms but only with significant coordination. In the computer industry, for example, there is a high degree of disaggregation of activities across different types of producers (e.g. producers of microprocessors, displays, hard drives, software), yet the interfaces between these components are of variable standardization. Though some interfaces are non-proprietary and highly standardized, requiring little coordination (e.g. USB ports), most of the other interfaces are imperfect or incorporate elements of proprietary control, requiring firms to engage in some form of negotiation and collabo-ration (such as licensing, standards consortiums, etc.).
When an industry demonstrates sufficient complexity that firms are motivated to disaggregate the product system into more manageable components, yet those compo-nents are also imperfectly separable, the firms in the industry will experience a high need for coordination.
Centralization of Control
Whereas the need for coordination in a district refers to the degree to which members must actively interact to manage their interdependencies, centralization of control refers to the degree to which one or more parties have disproportionate authority or influence over which interactions take place and how they are carried out. Some industrial districts exhibit extremes of centralization of control, such as the aerospace district in Seattle. To
understand this phenomenon, we need to examine the factors that lead to concentration of power in a single (or few) district member(s). The two primary factors we consider here are architectural control, and high minimum efficient scale.[4]
Architectural control. Even in industries in which activities are highly separable, the control over the architecture of the final system may be highly concentrated within the hands of a single (or few) firms (Brusoni et al., 2001). For example, when a firm retains control over a dominant technology standard in an industry, it may be able to exert some degree of architectural control over the system in which the technology is embedded (Schilling, 2000). Microsoft’s control over the dominant personal computer operating system gives it a vast amount of architectural control in the personal computer industry. Through selective compatibility, it can influence which other firms do well and which do not, and it can ensure that it has a number of different avenues from which to profit from the platform (Schilling, 2009). The firm can also control the rate at which the technology is upgraded or refined, the path it follows in its evolution, and its compatibility with previous generations. When a district forms around an industry that is characterized by such concentrated architectural control, the firms that possess control can rise to become hubs that dictate much of the behaviour in the district due to their large bargaining power.
High minimum efficient scale. If one or more stages of the value chain of an industry has very high minimum efficient scale, then by necessity the industry will be characterized by one or a few large players for those stages of the value chain. For example, automobile and aircraft manufacturers are essentially integrators that assemble multiple subsystems, most of which are outsourced to specialized producers. For such complex, capital-intensive products, the number of integrators is typically limited relative to the number of sub-system producers, and the integrators’ access to the end users creates a great deal of bargaining power for the integrators (Coff, 1999). The integrators do not need to control or master the subsystem technologies, yet they can exercise control over subsystem producers due to their control of the overall system.
INDUSTRIAL DISTRICT ARCHETYPES
As we show in Figure 1, need for coordination and centralization of control are continu-ous dimensions. However, high and low values of these dimensions represent districts that come into being for entirely different reasons, and in which the logic of competition, and by implication the sources of competitive advantage for firms, vary significantly. Our ultimate goal is to examine the competitive implications for firms of locating in different types of districts. Therefore in this section, we introduce four archetypes that represent combinations of the extreme values of our two dimensions. In our discussion section, we discuss the issue of ‘mixed types’ where districts fall in mid-range values of our dimen-sions. In the remainder of this section we outline the key characteristics of each of our archetypes, discuss how they may emerge, explain the costs and benefits associated with locating in them, and examine the competitive-advantage related implications. Our arguments are summarized in Table I.
Quadrant 1: Low Centralization–Low Coordination[5]Archetype
The low centralization–low coordination archetype is akin to Marshall’s original con-ception of industrial districts, Markusen’s (1996) ‘Marshallian districts’, and Gordon and McCann’s (2000) ‘pure agglomeration model’. The emergence of this archetype is largely due to location-driven factors such as local resource endowments (e.g. mineral deposits), zoning laws or access to transportation infrastructure making the location obligatory (e.g. red-light districts), or proximity to an important customer base drawing companies to the location (e.g. the hotel district near Niagara Falls). Once a threshold number of firms accumulate in the particular geography, district growth becomes self-reinforcing due to the emergence of positive externalities (explained below), and contin-ues until the emergence of diseconomies of agglomeration.
The low centralization–low coordination archetype is typically composed of small, locally-owned firms. Low technological complexity and relatively stable product char-acteristics eliminate the need for high levels of cooperation between firms and make price
QUADRANT 2 QUADRANT 3 QUADRANT 4 QUADRANT 1 HIGH LOW LOW HIGH Centralization of Control
Need for Coordination
Logic of intra-district competitive advantage: Better positioning within the
local collaboration network
Logic of intra-district competitive advantage: Increasing bargaining power
against the hub.
Logic of intra-district competitive advantage: Benefitting differentially from
externalities
Logic of intra-district competitive advantage: Better access to and
utilization of the knowledge from research institutions (in research parks), better utilization of infrastructure (in industrial parks)
Table I. Industrial district archetypes and attributes Industrial district archetype a Low need for coordination, Low centralization of control High need for coordination, Low centralization of control High need for coordination, High centralization of control Low need for coordination, High centralization of control Primary mechanism of emergence Firms pulled into a specific location due to the presence of input factors or demand. History dependent exchange relationships pulling firms together in the same geography. Hub attracting suppliers into its location and spinof fs from the hub. Local governments, business interests and research institutions coming together to build industrial or research parks and trying to attract ‘tenants’. Also spinof fs from research institutions and existing tenants. Structure Many small or medium-sized firms w ith no single firm holding significant market power. A combination of small, medium, and relatively large firms with no single firm holding significant market power. One (or a few) powerful, vertically integrated hub firm(s) surrounded by small, specialized suppliers. A combination of small, medium, and relatively large firms. Members are often branches of large, global firms headquartered outside the district.
Nature of relationships between firms in the district • Primarily transact within district. Few firms sell to outside buyers. • Predominantly vertical contracts between buyers and suppliers. • Primarily transact within district. Some firms sell to outside buyers. • Vertical contracts between buyers and suppliers as well as horizontal relationships (particularly among technology firms). • T he hub transacts globally, suppliers rely on business from the hub. • T he hub engages in arm’s-length exchanges with the majority of suppliers and cooperative relationships with a few (1st tier) suppliers in the district. • V ertical contracts between hub and suppliers. • M inimal interaction (vertical or horizontal) between entities in the district. • Entities interact regularly with the governing body of the district. Predominant form of governance • A rm’s length market exchanges. • N o cooperation among firms beyond what is in their economic interests in an atomized competitive environment. • G eographically-bounded network organization • Strong norms o f cooperation and social exchange (i.e. local institutional environment) maintained by trade associations and guilds. • H ierarchical governance by the hub. • Supplier behaviour is regulated by the structures and the sanctions that the hub puts in place. • H ierarchical governance by the sponsor of the district. Examples Xindu furniture district in Southwest China; Niagara Falls hotel district; wine district in Burgundy, France; textile district in Reutlingen, Germany; new media district in New York City. Ceramic tile district in Castellon, Spain; knitwear cluster in Modena, Italy; packaging valley in Bologna, Italy; motion picture district in Hollywood, CA; Silicon Valley in CA; Silicon Hills in TX; Silicon Wadi (Israel); Silicon Fen (England); Bangalore (India). Aerospace district in Seattle; automotive districts in Detroit, US and Belo Horizonte, Brazil; Toyota City in Japan; military industrial district in Colorado Springs; biopharmaceutical district in central New Jersey; business machines district in Ivrea, Italy. State-owned and/or run industrial parks such as the China–Singapore Suzhou Industrial Park, Senica Industrial Park in the Slovak Republic, Kaesong Industrial Park in North Korea.
Table I. Continued Industrial district archetype a Low need for coordination, Low centralization of control High need for coordination, Low centralization of control High need for coordination, High centralization of control Low need for coordination, High centralization of control Benefits associated with locating in the district Labour, supply, knowledge, and demand externalities. Labour, supply, knowledge, and demand externalities; knowledge creation and flexible specialization advantages due to network organization. For suppliers : Labour and knowledge externalities, lower transportation and transaction costs. Pecuniary externalities (e.g. cheaper of fice space, tax benefits, research grants), labour externalities, support from local government and research institutions, access to specifically designed infrastructure, knowledge spillovers and high frequency of knowledge collaboration with research institutions.
Costs associated with locating in the district Increased competition due to co-location; disproportionate appropriation of returns to investments that create the externalities. Increased competition due to co-location, high levels of embeddedness prevent firms from upgrading their resource positions in the face of environmental changes. For suppliers : Increased competition due to co-location, abuse by the hub Friction between governing body and tenant firms. Branches having trouble reconciling corporate policies with the governing body’s policies. Increases in prices of locating in industrial and science parks, higher labour costs. Competitive advantage of district firms vs. isolated firms Externalities. • Externalities. • U n-traded interdependencies and architectural knowledge. • Externalities. • A mplified knowledge spillovers when the hub’s policies create a cooperative environment in district. Depends on the policies of the governing sponsor. Intra-district dif ferences in competitive advantage • Absorptive capacity impacts ability to benefit from knowledge spillovers. • R educing knowledge leakages impacts net knowledge spillover benefits. • Absorptive capacity impacts ability to benefit from knowledge spillovers. • Reducing knowledge leakages impacts net knowledge spillover benefits. • C entrality/brokerage position increases advantage. • Experience at managing ties increases advantage. • M aintaining a m ix of arm’s length and embedded ties reduces resource-renewal-related disadvantages. • Absorptive capacity impacts ability to benefit from knowledge spillovers. • R educing knowledge leakages impacts net knowledge spillover benefits. • Stable relationship with hub is source of advantage and the strength of the advantage increases with duration of the relationship. • N ot relevant for firms that only have branch of fices inside the district. For standalone firms, dif ferential relationships with the governing sponsor of the district.
Table I. Continued Industrial district archetype a Low need for coordination, Low centralization of control High need for coordination, Low centralization of control High need for coordination, High centralization of control Low need for coordination, High centralization of control Newcomers’ access to the benefits that the district of fers Newcomers to the district have immediate and full access to the benefits associated with externalities. Newcomers have to make significant investments in technology development and relationship building before they can become a part of the cooperative network and enjoy the associated benefits. Newcomers have to make significant investments in technology development and relationship building before they can establish a relationship with the hub and enjoy the associated benefits. Newcomers to research parks need to establish relations with the sponsoring research institution. a Shaded circles represent d ownstream firms; squares represent branches of firms; dashed lines represent cooperative relationships.
competition key. District firms transact primarily locally, with minimal use of contracts or cooperative relationships with outside firms although a few firms may sell to outside buyers. Most intra-district transactions are vertical contracts, and are more like arm’s-length exchanges in spot markets than long-term relationships. The district’s competitive environment resembles perfect competition since no firm is large enough to influence the district’s competitive dynamic and cooperative relationships are largely missing.
Most examples of this archetype are characterized by a single dominant industry that is low-tech and often labour intensive such as furniture manufacturing (e.g. Xindu district in Southwest China; Tan et al., 2009), restaurants (e.g. Chinatown in New York City), hotels (e.g. Niagara Falls hotel district; Ingram and Inman, 1996), wine (e.g. family owned wineries in Burgundy, France), textiles (e.g. Reutlingen district in Germany), and new media (e.g. Silicon Alley; Arıkan, 2008).
Benefits associated with locating in a low centralization–low coordination archetype. The firms in a low centralization–low coordination archetype are co-located primarily due to external reasons (e.g. geographic concentration of input-supplies or demand) rather than gover-nance related benefits geographic proximity creates as in a low centralization–high coordination archetype (explained later). The primary benefits district firms enjoy are positive externalities that arise from simple proximity.
The first is a labour externality which means district firms gain easier access to specialized labour at more affordable prices. A local labour pool with industry-specific skills emerges because local workers develop industry-specific skills and individuals from outside with industry-specific skills are attracted to the district (David and Rosenbloom, 1990). The second externality is a supplier externality which means dis-trict firms gain access to a large number of specialized inputs at lower costs. Suppliers can gain economies of scale and economize on transportation and transaction costs by locating close to agglomerated firms. In time, they become increasingly more special-ized towards the needs of district firms and are forced to share their cost savings with their buyers due to increased local competition. The third externality is knowledge spillovers. Proximity facilitates knowledge (particularly tacit knowledge) transfers between district firms due to intra-district labour mobility, personal relationships, fre-quent face-to-face interactions, and a shared culture and language among local firms ( Almeida and Kogut, 1999; Jaffe et al., 1993). The fourth externality is a demand externality. When firms agglomerate, they attract greater numbers of customers than do isolated firms since co-location reduces the search costs for consumers and increases the overall demand in the district.
Costs associated with locating in a low centralization–low coordination archetype. The first cost relates to increased competition due to co-location. The presence of externalities creates incentives for co-location and stimulates entry into the district. Over time, over-entry creates intra-district crowding and increases local competitive pressures (Sorensen and Sorenson, 2003), making survival in the district extremely difficult (Staber, 1998). Crowding also creates diseconomies of agglomeration as costs of living and doing business rise with increased entry (Pouder and St. John, 1996). Raises in such costs may offset or even reverse the district’s pecuniary benefits.
The second cost relates to the extent to which the firms that contribute to the creation of externalities are able to appropriate the associated returns. To illustrate, a firm that has a better reputation than other district firms is likely to contribute more to the demand externality by attracting more customers to the district yet faces a higher risk of losing its customers to other district firms (Kalnins and Chung, 2004).
Low centralization–low coordination archetype and competitive advantage: district firms versus isolated firms. The research on low centralization–low coordination archetypes has traditionally emphasized the labour, supply, knowledge, and demand externalities as sources of competitive advantage for districts firms against isolated firms. Below, we discuss bound-ary conditions for firms to reap these advantages.
Firms in a low centralization–low coordination archetype are only likely to reap labour externality advantages over non-district firms when (1) the skills in question are relatively rare and take time to accrue, and (2) individuals are reluctant to leave their local communities. When these two conditions hold, isolated firms bear higher labour costs (related to labour search, wages, and training) or accept less-skilled labour. If either of the two conditions does not hold, neither will the advantage. For example, if the jobs in a district require basic skills that typical high school or college graduates are likely to possess (e.g. waitressing in restaurant districts in large metropolitan areas), or skills that can be gained quickly with minimal training (e.g. sewing by hand or with a sewing machine in textile manufacturing districts in China), then the creation of a local labour pool will confer little advantage to a district firm over non-district firms. In contrast, districts characterized by work that requires specialized skills (e.g. cutlery making in Germany’s Solingen district) will benefit more from labour externalities. Furthermore, though individuals are often rooted to their local communities, some outside firms can mitigate such mobility concerns by, for example, offering a highly desirable location (e.g. universities in locations with relatively better climate and/or urban infrastructure attract-ing high quality faculty) and thus attractattract-ing skilled labour easily, or by employattract-ing individuals remotely (e.g. through telecommuting as exemplified by newspapers employ-ing reporters from distant locations) and thus tappemploy-ing into non-proximate labour pools. Proposition 1a: The labour externality advantages that firms in a low centralization–low coordination archetype enjoy over non-district firms will be limited to the extent that the skills required by the industry are not specialized and take little time to accrue. Proposition 1b: The labour externality advantages that firms in a low centralization–low coordination archetype enjoy over non-district firms will be limited to the extent that labour is relatively mobile.
Proposition 1c: The labour externality advantages that firms in a low centralization–low coordination archetype enjoy over non-district firms will be limited to the extent that non-district firms are capable of employing labour remotely.
Supply externalities are subject to similar boundary conditions. If the supplies required by the industry are specialized in a way that makes them costly or time-consuming to
produce, and distance from a supplier creates significant transaction and/or transpor-tation costs (as is the case in specialized footwear manufacturing machinery and moulds for the footwear district in Sinos Valley, Brazil), then the large specialized supplier pool could provide a competitive advantage to district firms over non-district firms. By contrast, the advantage will not be substantive if the industry requires only generic inputs available from suppliers in a wide range of locales (e.g. computers as the most important input to content based internet companies in New York’s Silicon Alley district) or supplies can be obtained remotely with low transaction costs (because for instance, the quality of suppliers and their products is easily assessed remotely or is highly regulated by external standards bodies), and with relatively low transportation costs (i.e. when the value-to-bulk ratio of a product is very high, as with microprocessors).
Proposition 2a: The supplier externality advantages that firms in a low centralization– low coordination archetype enjoy over non-district firms will be limited to the extent that the supplies required by the industry are not specialized and/or readily available in multiple locales.
Proposition 2b: The supplier externality advantages that firms in a low centralization– low coordination archetype enjoy over non-district firms will be limited to the extent that supplies can be obtained remotely with low transaction costs and with low trans-portation costs.
Low centralization–low coordination archetypes only provide a knowledge externality advantage to member firms to the degree that proximity plays an important role in knowledge spillovers. The degree to which proximity will play a role in the diffusion of knowledge will depend first on how complex and tacit the knowledge is (Storper and Venables, 2004). Complex and tacit knowledge requires frequent and intense face-to-face interaction to facilitate its exchange. Knowledge that is simple and tacit, however, might be transferred through relatively brief or infrequent interaction (i.e. without requiring co-location), and knowledge that is codifiable might be transferred easily across great distances in written form. For example, we would expect knowledge spillover advantages to be much more significant in a district that employs biotechnology (e.g. a medical devices district) than in a district that employs basic manufacturing technology (e.g. a furniture manufacturing district).
Second, the degree to which a firm will benefit from knowledge externalities will be influenced by its absorptive capacity (Cohen and Levinthal, 1990). If non-district firms have significantly greater absorptive capacity than district firms (e.g. through greater cumulative investment in R&D or market experience), they might be better able to assimilate and utilize knowledge externalities, irrespective of where those externalities are generated. For example, it is likely that Microsoft (located in Seattle), due to its massive repository of knowledge and experience in the software industry, is able to assimilate and utilize some knowledge spillovers generated in Silicon Valley better and faster than software firms located in Silicon Valley.
Third, though proximity greatly facilitates knowledge spillovers, firms outside the district may find alternative ways to access the knowledge within the district (Zaheer and
George, 2004). For example, access to knowledge that resides in a distant geography is one of the primary reasons why geographically distant firms engage in collaborative relationships as Rosenkopf and Almeida (2003) demonstrated in the semiconductor industry. Establishing ‘probes’ in the district through such collaborative relationships may give non-district firms access to the knowledge that resides in the district.
Proposition 3a: The knowledge-spillover advantages that firms in a low centralization– low coordination archetype enjoy over non-district firms will be limited to the extent that the knowledge spilled in the district is simple and explicit.
Proposition 3b: The knowledge-spillover advantages that firms in a low centralization– low coordination archetype enjoy over non-district firms will be limited to the extent that non-district firms have equal or greater absorptive capacity than district firms. Proposition 3c: The knowledge-spillover advantages that firms in a low centralization– low coordination archetype enjoy over non-district firms will be limited to the extent that non-district firms are embedded in collaborative networks that can tap into the district’s knowledge base.
Finally, demand externalities may constitute a source of advantage only when an industry has a high level of product heterogeneity (and an associated need for customers to do higher levels of search), and proximity plays a key role in that search (as in the Diamond District in New York City). Other districts do not benefit as much from demand externalities as their products are relatively homogenous, and/or the ways firms sell their products (e.g. through intermediaries (such as distributors, wholesalers, sales representatives), catalogues, trade shows, internet) undermines the importance of geo-graphic proximity in terms of generating demand externalities (e.g. plastics district in North Central Massachusetts).
Proposition 4a: The demand externality advantages that firms in a low centralization– low coordination archetype enjoy over non-district firms will be limited to the extent that there is low need for search (i.e. products are largely homogenous).
Proposition 4b: The demand externality advantages that firms in a low centralization– low coordination archetype enjoy over non-district firms will be limited to the extent that proximity does not play a key role in product search (e.g. when product com-plexity is low or product attributes are easily evaluated remotely).
Low centralization–low coordination archetype and competitive advantage: intra-district firm differences. Given that the benefits that accrue to firms in a low centralization–low coordination archetype are external to firms, the district essentially has open membership and simple co-location is likely to ensure equal access to the benefits of agglomeration. Since all district firms will have access to the labour, supply, and demand externalities, resource-based view’s rareness condition (Barney, 1986) is not met and access to these externalities
fails to provide firms in the district with a competitive advantage against other district firms. However, it is possible for knowledge spillovers to be a source of intra-district heterogeneity since firms can benefit from such spillovers differentially.
First, a firm with more advanced knowledge stocks (i.e. higher absorptive capacity) than other district firms may reap knowledge spillover advantages over other district firms. This can lead to a self-reinforcing effect wherein firms with initially greater knowledge stocks also have greater access to knowledge spillovers. Second, there may also be differences in the degree to which firms lose valuable knowledge through spill-overs. Firms that are able to better protect their knowledge from spilling out while enjoying inward knowledge spillovers from other firms are likely to have an advantage over other district firms. A large portion of knowledge spillovers occurs through labour mobility (Almeida and Kogut, 1999). Therefore, firms that are able to keep their employ-ees from leaving the firm (e.g. through offering a favourable work environment, attrac-tive compensation, or seniority based promotion schemes), or ensure that leaving employees do not share valuable knowledge with competitors (e.g. through exclusivity or secrecy clauses in employment contracts), are likely to reduce knowledge leakages and gain net knowledge spillover advantages over other district firms.
Quadrant 2: Low Centralization–High Coordination Archetype
The low centralization–high coordination archetype is akin to Markusen’s (1996) ‘Ital-ianate district’ and Gordon and McCann’s (2000) ‘social network model’. The high need for coordination may be due primarily to technological complexity (e.g. as in high tech districts that emerge to exploit a general-purpose technology (e.g. biotech, micro-electronics, nanotech) in multiple industrial contexts (Bresnahan and Trajtenberg, 1995)), or to rapidly changing consumer tastes (e.g. as in clothing districts in Northern Italy). In the former, individual firms simply cannot possess all the technology they need and/or have a lot to gain from exploiting complementarities with other firms’ technolo-gies. In the latter, vertical integration limits flexibility to respond to rapidly changing customer needs, and a pure market-like exchange environment does not provide the level of cooperation required to offer high quality, customized products rapidly. In response, firms disintegrate, specialize in particular activities (or technologies), and engage in long term relationships with other similarly specialized firms to deliver finished products. The district emerges as a new form of governance that solves the dual problems of a need for flexibility and specialization (Piore and Sabel, 1984).
As in the case of low centralization–low coordination archetype, the low centralization–high coordination archetype consists primarily of small and medium sized firms due mainly to disintegration and specialization by firms. While some of the district’s firms may in time grow quite large, no firm grows big enough to ‘run’ the district as in a high centralization–high coordination archetype (explained later). To put it differently, the district does not ‘revolve around’ one or a few firms.
Geography plays a fundamentally different role in the emergence of a low centralization–high coordination archetype than it does in a low centralization–low coordination archetype. In a low centralization–low coordination archetype, geography constitutes a pull for firms due to a supply of inputs or the presence of demand. Thus the
co-location of the firms is an emergent outcome, rather than the primary intention for firms. In a low centralization–high coordination archetype, co-location is intentional as it provides governance-related benefits. When firms intentionally increase their depen-dence on other firms (by disintegrating and specializing) to respond to the dual pressures of flexibility and specialization, opportunism becomes a significant problem. Geographic proximity increases firms’ ability to monitor each other. Furthermore it makes instances of opportunism highly visible to other firms in the same geography which creates a major deterrent since a firm that is known to engage in opportunistic behaviour will have difficulty finding partners to do business in the district. This means that firms’ reputa-tions, trust and institutional norms of cooperation that create a logic of mutualism in exchange relationships become key elements of coordination and governance in the district (this contrasts with the primarily market-based governance in a low centralization–low coordination archetype and hierarchical governance by the hub in a high centralization–high coordination archetype). To put it differently, the low centralization–high coordination archetype is characterized by a geographically-bounded network form of governance (Powell, 1990).
Intra-district transactions are primarily vertical contracts, although horizontal rela-tionships (especially in the case of high need for coordination triggered by technological complexity) are also common. Suppliers may become increasingly integral as they become a part of the product design process (Harrison, 1992). District firms may sell their products to outside buyers. In contrast to a low centralization–low coordination arche-type where intra-district exchanges are largely arm’s length, inter-firm interactions in a low centralization–high coordination archetype are characterized by high levels of coop-eration, trust, mutualism, and a long-term orientation. Trade associations or guilds play a highly important role in strengthening/enforcing local norms of cooperation and coordinating intra-district exchanges.
The best examples of this archetype are some of the well known, craft-based districts such as the ceramic tile district in Castellon, Spain (Albors, 2002), the knitwear district in Modena, Italy (Lazerson, 1995), ‘packaging valley’ in Bologna, Italy (Boari, 2001), the motion picture district in Hollywood (Scott, 2002), and high technology districts such as Silicon Valley in California (Saxenian, 1994), Silicon Hills in Austin (Texas), Silicon Wadi in Israel, Silicon Fen in England, and Bangalore district in India.
Benefits associated with locating in a low centralization–high coordination archetype. Firms in a low centralization–high coordination archetype enjoy many of the same externality benefits accrued in a low centralization–low coordination archetype. They also enjoy additional benefits due to better rates of knowledge creation (in the case of high need for coordi-nation due to knowledge complexity) and flexible specialization (in the case of high need for coordination due to environmental complexity) (Harrison, 1992). In the former, technologically specialized firms exploit knowledge complementarities better due to higher frequency and effectiveness of inter-firm knowledge partnerships facilitated by geographic proximity (Arıkan, 2009). In the latter, each firm is able to become more narrowly specialized, enabling learning curve advantages and reduced fixed-asset com-mitments. The overall production system becomes more modular, enabling inputs and processes to be mixed and matched to rapidly respond to changes in customer tastes or
supplier inputs (Schilling and Steensma, 2001). Firms also benefit from lower transaction costs due to their increased knowledge and trust of their partners.
An important difference between a low centralization–low coordination archetype and a low centralization–high coordination archetype is that in the former, benefits of locating in the district are not conditional upon the nature of relationships between firms. The low centralization–low coordination archetype district survives and provides the externality benefits as long as the location based factors (i.e. input supply or presence of demand) are in place. In contrast, in a low centralization–high coordination archetype, benefits are entirely conditional upon the nature of intra-district relationships. In the absence of inter-firm cooperation and an appropriate institutional environment to prolong it, benefits beyond externalities such as higher rates of knowledge creation, lower transaction costs, flexible specialization, fast market response times, and higher quality products do not materialize.
Costs associated with locating in a low centralization–high coordination archetype. Crowding effects may also emerge in a low centralization–high coordination archetype. The bigger problem though is created by the high levels of embeddedness observed in a low centralization–high coordination archetype’s network organization. Embeddedness in the district’s cooperative network may limit district firms’ search for new information to the information that network partners hold. As district firms engage in repeated inter-actions with their long-term partners, they reference each other exclusively while making strategic decisions and eventually get more insulated from information outside the network (Uzzi, 1997). Consequently, they become increasingly homogenous with respect to their resource positions and beliefs about their industry (Pouder and St. John, 1996). In the face of major environmental changes, such homogenous macro-cultures are likely to cause district firms to suffer from spatial myopia and collective inertia, and hold on to obsolete resources or fail to develop new ones commensurate with new environmental demands (Teece et al., 1997) (e.g. see Glasmeier’s (1991) account of the luxury watch industry in Switzerland).
Low centralization–high coordination archetype and competitive advantage: district firms vs. isolated firms. Firms in a low centralization–high coordination archetype have an advantage over isolated firms because first, previously described externalities are also present here. The more important source of advantage, however, is the network organization. Within a low centralization–high coordination archetype firms form cooperative horizontal relation-ships with other district firms to access complementary resources (or technologies), and engage in long term relationships with their suppliers. These relationships involve vol-untary tacit-knowledge transfers facilitated by trust, shared conventions, rules, and language. Storper (1995) argues that such relationships constitute ‘untraded interdepen-dencies’ and represent a district specific source of competitive advantage. Similarly, Tallman et al. (2004, p. 265) argue that over time, district firms develop an inter-firm stock of architectural knowledge which ‘includes understandings of reciprocity, reputa-tion, interdependencies, and the other relational aspects of the social system of the knowledge cluster – how members relate to each other as they exchange . . . knowledge, cooperate, compete and build the cluster into a viable unit for analysis’. Non-district
firms have to either be more vertically integrated and lack the specialization/flexibility advantages of district firms, or they must transact with others in the absence of the strong norms of communication and cooperation present within districts. The un-traded inter-dependencies and the architectural knowledge that characterize a low centralization– high coordination archetype are situated in time and space within district-specific communities of practice, and are only accessible to the firms that are a part of the district’s cooperative network. Accordingly, they satisfy the resource-based view’s value, rareness, inimitability, and non-substitutability conditions at the district level and provide district firms with a sustainable competitive advantage against non-district firms. However, an important boundary condition for this advantage is the sustainability of the local norms of cooperation.
As crucial as norms of cooperation and resulting trust among low centralization–high coordination archetype firms may be, competitive challenges make the development of cooperative norms extremely difficult while creating numerous reasons to break them once established (Florida and Kenney, 1990). High levels of trust between district firms cause returns to opportunism to increase significantly, which creates stronger incentives for firms to break cooperative norms. The situation worsens during periods of low environmental munificence and higher competitive pressures. Under these conditions, a low centralization–high coordination archetype faces the danger of opportunism on behalf of a few firms creating waves of mistrust and deteriorating the district into what Mesquita (2007, p. 72) terms ‘immature clusters’ characterized by slow growth and little innovation. The importance of the creation and maintenance of an appropriate institu-tional environment, particularly in the face of environmental adversity, is documented in Alberti’s (2006) detailed examination of the decline of the Como Silk District in Italy. Thus, the sustainability of advantages that firms located in a low centralization–high coordination archetype enjoy against non-district firms is strongly related to the sustain-ability of an appropriate institutional environment for cooperation within the district. Such an institutional environment might include sanctions that prevent and punish opportunism, and instruments (e.g. regional trust facilitators) to re-establish cooperative norms when they are broken. Effective operation of trade associations or guilds is also key for maintaining cooperative norms.
Proposition 5: The advantages due to un-traded interdependencies and district-level architectural knowledge that firms in a low centralization–high coordination arche-type enjoy against non-district firms will be limited to the extent that firms in the district fail to create and maintain an institutional environment that reinforces strong cooperative norms.
Low centralization–high coordination archetype and competitive advantage: intra-district firm differences. Firms in a low centralization–high coordination archetype may reap differential advan-tage from knowledge spillovers due to their absorptive capacity and ability to reduce knowledge leakages. Furthermore, there may be intra-district differences due to: (1) firms’ differential positions in their cooperative networks; (2) their ability to productively manage their intra-district relationships; and (3) the mix of their network ties. We explain these below.
A firm’s position in the district’s cooperative network is directly related to the value of its resources. Firms that have more to offer to partners are likely to attract more partners and be more embedded in the district’s cooperative network (Ahuja, 2000; Stuart, 1998). Two types of network positions are particularly likely to yield an advantage for the firms that hold them. First, a firm with a highly central network position has access to a larger pool of knowledge and resources within the district, and has a greater ability to influence resource distribution in the network, compared to firms in more peripheral positions (McEvily and Zaheer, 1999). Second, a firm that bridges two or more otherwise uncon-nected firms (or groups of firms) in the district or that has connections to both district and non-district firms (i.e. a brokerage position), has access to unique combinations of knowledge, and can control the flow of information and other resources between those firms (Burt, 1992; Hargadon, 2003). Both of these positions constitute a valuable and rare resource and can be a source of competitive advantage for firms within the district (Gulati et al., 2000). In addition, advantages arising from network position are likely to be sustainable because network position is not easily imitable as networks evolve in a highly path-dependent manner (Gulati and Gargiulo, 1999). Ahuja (2000) suggests that the only way for a newcomer or an incumbent that has not been a part of the relational network to break into the weave of the network may be to generate a technological breakthrough. Thus contrary to a low centralization–low coordination archetype, a low centralization– high coordination archetype does not have open membership. Both access to the network (which requires valuable resources), and a favourable position for those that do have access to the network can take considerable time and effort to attain. The difficulty of securing a favourable position within the district’s cooperative network makes such a position a source of competitive advantage for a district firm against other firms in the district.
District firms may also vary in their ability to make cooperative relationships work and benefit from them. Cooperative relationships are replete with problems related to the choice of governance structure, transaction and coordination costs, and knowledge transfer. Firms are likely to learn how to deal with these problems as they gain experience in how to manage and benefit from cooperative relationships (Kale and Singh, 2007; Zollo et al., 2002). The extent to which a district firm benefits from its position within the district’s cooperative network is a function of its experience in managing cooperative ties. The more experience the firm has, the more it will benefit from being a member of the local cooperative network.
Finally, district firms can differentiate themselves by maintaining an appropriate mix of embedded and arm’s-length ties with firms in and outside the district. This type of mix helps a firm enjoy the benefits of embeddedness while at the same time giving it access to independent market information through arm’s-length ties and consequently making it less vulnerable to environmental jolts (Uzzi, 1997).
Quadrant 3: High Centralization–High Coordination Archetype
The high centralization–high coordination archetype is reminiscent of Markusen’s (1996) ‘hub and spoke’ and ‘state anchored’ districts. It typically forms around one or a few large firms that have architectural control over a product that is characterized by high technological complexity and/or high minimum efficient scale. The large entity
(‘the hub’ hereafter) both draws suppliers to its locale (either passively, or through shaping suppliers’ location decisions), and creates local suppliers through spin-offs (Klepper, 2007). Due to the large role a hub may play in the economic development of a region, local governments try to attract such ‘anchor tenants’ (Agrawal and Cockburn, 2003) to their regions by providing financial incentives such as tax breaks.
Most suppliers in the district rely significantly (if not exclusively) on the business from the hub, but the hub is not similarly dependent on local suppliers as it transacts globally (Gray et al., 1996). The asymmetrical dependence relationship and the hub’s size give the hub a large bargaining power against the local suppliers. Therefore, the nature of exchanges in the district and the economic prosperity of the district depend crucially on the hub’s strategies (Carbonara, 2002). Due to this characteristic, the primary form of governance in the district can be thought of as hierarchical governance[6]by the hub in contrast to market governance in a low centralization–low coordination archetype and geographically bounded network governance in a low centralization–high coordination archetype.
Most relationships are vertical supplier–buyer relationships between the hub and its suppliers. Typically, the hub establishes a limited number of first-tier suppliers with which it builds close, long term relationships (including equity ownerships). Exchanges with lower tier suppliers are increasingly more arm’s length-like. The horizontal rela-tionships between the suppliers are largely determined by the policies of the hub. Some hubs create an environment where the suppliers engage in cut-throat competition with each other (Gray et al., 1996). Other hubs will foster cooperative relationships and knowledge sharing among suppliers (Dyer and Nobeoka, 2000).
Some examples of a high centralization–high coordination archetype are the aero-space district in Seattle (Gray et al., 1996), automobile districts in Detroit (Klepper, 2007), Belo Horizonte in Brazil, and Toyota City in Japan (Dyer and Nobeoka, 2000), the military-industrial district in Colorado Springs, the biopharmaceutical district in central New Jersey, and the business machines district in Ivrea, Italy.
Benefits associated with locating in a high centralization–high coordination archetype. First, the hub creates externalities for local suppliers. The favourable employment terms that the hub offers attract high quality labour into the district and the suppliers enjoy the benefits of this labour pool due to mobility out of the hub or employee sharing policies by the hub (as exemplified by Toyota). The suppliers also benefit from knowledge spillovers from the technologically advanced hub. Second, both the hub and the suppliers benefit from transportation cost savings from co-location (e.g. as in automotive and aerospace dis-tricts). Finally, co-location reduces transaction costs by making it easier and cheaper for the hub to seek out suppliers, monitor their behaviour, and enforce contracts.
Costs associated with locating in a high centralization–high coordination archetype. As in the other archetypes, co-location around a hub increases local competitive pressures on suppliers. In addition, stable relationships between the suppliers and the hub, while potentially providing a source of competitive advantage for the suppliers, leave the suppliers open to abuse by the powerful hub. To illustrate, Mudambi and Helper (1998, p. 776) write about the automobile industry which is agglomerated in Detroit: ‘. . . suppliers to the
U.S. automobile industry have little expectation of being treated fairly by their custom-ers; further, a large plurality believe that if a competitor appeared with comparable quality and a lower price, their customer would switch as soon as technically feasible rather than working with them to match or better the competitor’. Rossetti and Choi (2005) report similar patterns in the aerospace industry which is agglomerated in Seattle. These accounts point to a situation where the hub creates seemingly stable relationships with suppliers to facilitate relationship-specific investments (including locating close to the hub) but then abandons them in pursuit of short term gains. This situation creates a small numbers bargaining problem and may lead to increased contracting costs as suppliers attempt to protect themselves from hold-up.
High centralization–high coordination archetype and competitive advantage: district suppliers vs. isolated suppliers. The hub enjoys all the benefits of the district to the fullest due to its large size, its global network of partners providing it with a position as the knowledge gateway between the district and the outside world, its market power over district suppliers, and its resulting position as the district’s leader. In contrast, the extent to which the smaller and less powerful suppliers enjoy the district’s benefits needs further elaboration.
Whether locating in a high centralization–high coordination archetype provides sup-pliers with a sustainable competitive advantage over isolated supsup-pliers depends on the hub’s policies and the types of relationships it cultivates within the district. In a district where relationships between the hub and local suppliers are mostly of the arm’s-length type, the benefits that accrue to local suppliers are limited to those in a low centralization–low coordination archetype. This is best exemplified by Seattle’s aero-space district. As the hub of the district, Boeing chooses to use its global network of suppliers to impose market discipline over local suppliers by pitting them against each other to achieve favourable exchange terms. Such a competitive environment practically eliminates any cooperation amongst local suppliers (Gray et al., 1996).
In contrast, if the hub engages in cooperative relationships with its local suppliers and cultivates cooperative relationships among suppliers, a network organization is likely to emerge within the district that amplifies the knowledge spillover advantages of being located within the district. This degree of knowledge sharing is akin to that achieved in a low centralization–high coordination archetype, except that in contrast to a low centralization–high coordination archetype where knowledge sharing is facilitated by institutional norms of cooperation reinforced by trade associations and guilds, in a high centralization–high coordination archetype, it is facilitated and managed by the hub. For example, Dyer and Nobeoka (2000) document how Toyota’s use of a supplier associa-tion, consulting/problem solving/learning teams, and employee transfers result in a high performance knowledge sharing network in Toyota City. That type of network organi-zation and the associated knowledge-related benefits may provide suppliers in the district with a sustainable competitive advantage over isolated suppliers.[7]
Proposition 6: The knowledge-related benefits that suppliers in a high centralization– high coordination archetype enjoy over non-district suppliers will be limited to the extent that the hub’s policies fail to cultivate and maintain a cooperative environment within the district.
High centralization–high coordination archetype and competitive advantage: intra-district firm differences. Suppliers in a high centralization–high coordination archetype are heterogeneous, based on: (1) the type of relationship they have with the hub; and (2) the extent to which they can benefit from it.
An arm’s-length relationship with the hub cannot be a source of sustained competitive advantage since it fails to satisfy the resource-based view’s rareness condition. What can be a source of sustained competitive advantage is a stable, long-term relationship with the hub (Dyer and Singh, 1998). The benefits of such a relationship to a particular supplier are three-fold. First, it facilitates the development of relationship specific assets and coordination/cooperation routines (which in turn leads to joint knowledge creation) (Zollo et al., 2002) that are inimitable to firms outside the relationship. The presence of relationship specific assets increases the dependency of the hub on the particular supplier and increases the supplier’s bargaining power against the hub. Second, it helps firms combine their complementary resources and generate greater rents than the sum of those that would be obtained from each firm’s resources individually. Finally, it facilitates the development of effective governance mechanisms that lower transaction costs (Gulati and Singh, 1998). Thus a stable relationship with the hub constitutes a valuable, rare, inimitable, and non-substitutable resource, and is a source of competitive advantage for a district firm against other firms in the district.
Several suppliers in a high centralization–high coordination archetype may have established stable relationships with the hub but suppliers benefit more from these relationships the longer they have been in the relationship. The development of rela-tionship specific assets and the ability to engage in joint learning occurs over time through repeated interactions. The longer the relationship the more the parties become familiar with each other’s idiosyncrasies, which makes it progressively easier for them to develop cooperation routines, learn from each other, and engage in joint knowledge creation (Lane and Lubatkin, 1998). In addition, a longer relationship reduces the possibility and/or extent of opportunistic behaviour by the hub as it is likely to increase the hub’s dependency on the supplier and replacement cost of the supplier.
A newcomer to a high centralization–high coordination archetype may start enjoying the benefits associated with externalities immediately. However, access to benefits that provide a basis for sustainable competitive advantage requires the newcomer to build a stable relationship with the hub. As in the case of a low centralization–high coordination archetype, establishing such a relationship requires the supplier to make major invest-ments in technology and relationship building to make itself an attractive partner to the hub.
Quadrant 4: High Centralization–Low Coordination Archetype
The high centralization–low coordination archetype represents a district characterized by a somewhat unusual combination of a low need for coordination, yet high central-ization of control. The best examples of such a district are stated-owned and run industrial parks in which the state plays a very active role in the governance of the district. For example, in the China–Singapore Suzhou Industrial Park (Wei et al., 2009),
the Singaporean government not only orchestrated the development of infrastructure and other location benefits for the district, it also actively imposed a ‘Singaporean operating system’ (a set of administrative principles and institutional practices) upon member firms that it believed would improve development and foreign investment within the district (Pereira, 2007).
A high centralization–low coordination archetype is typically ‘made’ rather than emergent as in the other three archetypes. It is often populated by branches of large, global firms (reminiscent of Markusen’s (1996) ‘satellite platforms’) rather than standal-one firms. Local governments build such districts in cooperation with local business interests and/or research institutions primarily for the purpose of local economic devel-opment and employment growth. They then try to attract large ‘tenants’ (through incentives) to establish presence in the district. The district grows as more tenants move in and small firms are spun off from existing tenants and research institution(s) (Markman et al., 2008). Though the members typically have no inherent vertical or horizontal dependencies (akin to a low centralization–low coordination archetype), control may be exerted over the district by a central governing body in efforts to foster synergies and spillovers, thereby jumpstarting the process by which positive externalities begin to accrue.
It is important to note that not all state-sponsored industrial parks or science parks would be considered high centralization–low coordination archetypes. In many such parks (e.g. North Carolina’s Research Triangle, Taiwan’s Hsinchu Science Park, and the Pureland Industrial Complex in New Jersey) the state provides only incentives such as tax benefits, infrastructure, low cost real estate, or capital, to create a location benefit. The state does not attempt to exert much control over the businesses leading to a district that looks much more like a low centralization–low coordination archetype than a high centralization–low coordination archetype.
Benefits associated with locating in a high centralization–low coordination archetype. Firms in a high centralization–low coordination archetype enjoy pecuniary benefits as research and industrial parks are usually created by local governments that are willing to provide financial incentives (e.g. cheaper office space, tax breaks, research grants) to attract tenants to these parks. The collaborative efforts of local governments, businesses, and research institutions to promote these parks create a favourable socio-economic envi-ronment for the district’s tenants. Second, firms enjoy significant labour externalities. In the case of research parks, graduates from the local research institution(s) provide a large pool of highly qualified workers. In the case of industrial parks, production workers are attracted to the park due to the agglomeration of production facilities. Tenants of industrial parks also enjoy the benefits of a physical infrastructure (e.g. transportation, waste management, etc.) built specifically according to their needs. Finally and perhaps most importantly, firms in research parks enjoy knowledge spillover benefits. Even though intra-district labour mobility is minimal in this type of district (Markusen, 1996), the parks may be designed in a way that university scientists and business units share the same buildings. In such settings, the frequency of face-to-face encounters is maximized (Storper and Venables, 2004) and collaborative knowledge creation opportunities between research institutions and tenant firms’ R&D units abound. Such opportunities
are further strengthened by the supportive policies (to the extent they exist) of the sponsoring research institution and the local government.
Costs associated with locating in a high centralization–low coordination archetype. The imposition of centralized control over firms that have no inherent coordination needs between them can create some friction between the member firms and the governing body. Managers may resent adopting the policies or practices that are recommended or required by the state, or find that the policies and practices are suboptimal for their particular firm. While standardization of particular practices within the district facilitates exchange between members of the district, it may forfeit the benefits of firms using practices that are more specific to their activities, people, and systems. Furthermore, if the member firms are branches of global firms that are headquartered elsewhere, the managers of those branches may find it difficult to reconcile the demands of the district’s governing body with the demands of the corporate headquarters.
Firms in a high centralization–low coordination archetype may also suffer from raising labour and park maintenance costs (e.g. office space, installation and maintenance of infrastructure, joint park activities, etc.). However, research shows that when these costs become formidable, firms do not hesitate to move their branches outside of the research or industrial parks (Ferguson, 2004).
High centralization–low coordination archetype and competitive advantage: district firms vs. isolated firms. Firms in a high centralization–low coordination archetype can have an advantage over isolated firms because the labour, supplier, and knowledge externalities character-izing a low centralization–low coordination archetype are also present here. However, to the degree that centralized control facilitates more active transfer of knowledge between firms (as if often the aim of Science Parks) or more active cooperation in the sourcing of supplies (as is sometimes arranged in industrial parks), these districts may reap even greater knowledge externalities or supply-sourcing advantages than those in the low centralization–low coordination archetype district. Since the nature of such benefits is idiosyncratic to the type of policies and practices imposed by the governing body of the district, we merely raise these as possibilities rather than posing additional propositions.
DISCUSSION Contributions
Our goal in this paper was to examine how variance in the structure and governance of industrial districts affects the costs and benefits their members accrue, and the implica-tions of those costs and benefits for competitive advantage. By focusing on the dimen-sions of need for coordination and centralization of control, we were able to develop a theoretically grounded typology of districts. While our typology is consistent with previ-ous typologies (e.g. Markusen, 1996), it is significantly different from them in several ways.
