Int. J. Management Concepts and Philosophy, Vol. X, No. Y, XXXX
Size-competitive strength matrix for classifying organisations1 Juan Manuel Maqueira-Marín, José Moyano-Fuentes* and Sebastián Bruque-Cámara Department of Business Administration, Accounting and Sociology, University of Jaén, E.P.S. Linares, C/Alfonso X el Sabio, 28, 23700 Linares (Jaen), Spain Fax: +34 953 648 508 Email:
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[email protected] *Corresponding author Abstract: According to organisational ecology theory, the competition between organisations is a key process that can help to explain the vital rates of organisational populations. In turn, it is possible to observe the intensity of the competition through the size differences between the members of a population. This paper reviews the models that have analysed the influence of competition on survival under this approach, emphasising the important role played by organisational size. This allows us to identify the main interrelations between size and competition, and consequently propose a new matrix to classify and characterise organisations in four groups on the basis of these two variables. In order for this matrix to be useful to managers and consultants, this paper designs a methodology for positioning organisations within the matrix. This methodology can be used to guide strategic decisions for the future. Keywords: organisational ecology; strategic tool; size-competitive strength matrix; competitive intensity; survival, vital rates. Reference to this paper should be made as follows: Maqueira-Marín, J.M., Moyano-Fuentes, J. and Bruque-Cámara, S. (200X) ‘Size-competitive strength matrix for classifying organisations’, Int. J. Management Concepts and Philosophy, Vol. X, No. Y, pp.xxx–xxx. Biographical notes: Juan M. Maqueira-Marín is an Associate Professor and Researcher on Information Technology Adoption in the Department of Business Administration, Accounting and Sociology at the University of Jaén (Spain). He is currently conducting research on factors leading to Grid technology adoption. He has a wide experience as a practitioner in some technological firms such us Fujitsu Spain Inc. Currently he is involved as a student in the doctoral programme on Technology Management at the University of Jaén. José Moyano-Fuentes is a Professor of Management in the Department of Business Administration, Accounting and Sociology at the University of Jaén (Spain). He currently conducts research on the effect of the ownership structure on firm performance. He also has interests on the role of technology in organisations, with current emphasis involving social networks
Copyright © 200X Inderscience Enterprises Ltd.
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara influence on employees’ technology acceptance. His research has appeared in the Administrative Science Quarterly, Journal of Management Studies, International Journal of Management Reviews and Technology Analysis and Strategic Management. Sebastián Bruque-Cámara is a Professor of Management in the Department of Business Administration, Accounting and Sociology at the University of Jaén (Spain). He currently conducts research on organisational factors affecting IT adoption and social networks effects on workers’ acceptance of technological changes. He has been Visitor Researcher at the University of Nijmegen (The Netherlands) and his research has appeared in the European Journal of Information Systems, Internet Research, Journal of High Technology Management Research, Technovation and Technology Analysis and Strategic Management.
1
Introduction
From its early days, the theoretical approach of population ecology (Hannan and Freeman, 1977) has investigated the interrelations between size and competition to help explain foundation and mortality rates in organisational populations. Since Hannan and Freeman (1977) establish the size-based competition model, researchers have made attempts to reveal the true effects of size on competition among organisations, giving rise to the development of various models. Thus, the densitydependence model (Hannan, 1989) explains the effects of competition on the vital rates through the total number of organisations present in a population at any given time (the population density). The simplicity of the explanatory variable used in this model, however, leads to the development of other models that analyse the competition-survival relation through other size-based variables. The three main models focusing on the influence of the size variable on competition in order to estimate organisational birth and death rates are: (1) the mass-dependence model (Barnett and Amburgey, 1990); (2) the competitive intensity model (Barnett, 1997) and (3) the scale-based selection model (Dobrev and Carroll, 2003). The mass-dependence model considers the effects of the aggregate size of a population (or population mass) on survival (Barnett and Amburgey, 1990), ignoring the individual differences among organisations. The competitive intensity model does consider the effects of individual diversity on survival, using the product of the age and size of each organisation (Barnett, 1997). Finally, the scale-based selection model considers size as a representative variable of the firm’s strategy that is fundamental to understand the relation between competition and survival (Dobrev and Carroll, 2003). These models represent an important advance in the understanding of the complex interrelations between size and competition. However, there is a lack of a tool for demonstrating these interrelations that researchers can use to indicate the situation of a particular organisation with respect to these variables. The current work fills this gap. With this in mind, and from the organisational ecology perspective, the work builds a matrix to characterise the different types of organisation on the basis of the variables size and competition. This characterisation captures the main findings of the organisational
Size-competitive strength matrix for classifying organisations ecology school with regard to size-competition interrelations. The characterisation should prove useful to analysts, by helping them to identify where a particular organisation is located. The managers, by manipulating the size variable, can then consider moving their firm towards another position with its different competitive situation. This work is structured in seven sections, starting from the present introduction. The second section briefly reviews the different organisational ecology models that examine the relation between competition and survival, focusing on those models that consider the influence of the size variable. Attending to the main findings of the previous section, in section three we draw up the propositions which link size, competition and survival chances among organisations. Section 4 then introduces the proposed size-competitive strength matrix. Section 5 describes how to apply this matrix. Section 6 outlines the implications that using this matrix may have for the management of companies. The work ends with the conclusions section.
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Organisational ecology models based on the size effect
The concept of competition in organisational ecology refers to the struggle that arises when organisations depend on a set of limited environmental resources (Hannan and Freeman, 1977). The pioneering work of Hannan and Freeman (1977) already introduces the effect that size has on competition, considering that firms only compete against similarly sized companies, since these use similar strategies, structures and combinations of resources. Conceptually, direct competition emerges from this idea (Hannan and Freeman, 1989). This refers to organisations’ explicit recognition that they are competing against each one another. However, another type of competition exists, labelled ‘diffuse competition’, where organisations do not know exactly which organisations they are competing against. In organisational ecology, researchers offer different models that consider competition as a key process that influences organisations’ survival. The first model to appear is the density-dependence model (Hannan, 1989), which explains the evolution of organisational populations by means of two sociological processes: (1) diffuse competition and (2) legitimation. The model holds that these processes can be approximated by the population density (or number of firms in the population at any particular moment). According to this model, competition rises with that population density at an increasing rate, and an organisation’s probability of failure is directly proportional to the intensity of competition (Hannan and Carroll, 1992). But this model is limited as it is based on a variable (density) that does not consider important factors that affect competitive processes within the population. This leads to the appearance of other models that overcome this failing (Núñez and Moyano, 2004). Thus, the two types of competition models appear to build from variables that illustrate the existing competition in a population better (Núñez and Moyano, 2004). Competition models non dependent on the density make up a first group, such as: (a) the population dynamics model, which considers the influence that the number of foundations and failures occurring in the previous year has on a population’s competitive dynamics (Delacroix et al., 1989); (b) the mass-dependence model, which considers the competitive effects of the aggregate size of all the organisations in a population (Barnett
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara and Amburgey, 1990) and (c) the resource partitioning model, which considers the influence that the population’s level of concentration has on the competitive environment (Carroll, 1985). Models including effects that are external to the relation between competition and survival make up a second group. Apart from density, these models introduce new variables that can affect a population’s competitive dynamics. The age of the population and the age and size of the individual organisations are among these variables. The group includes: (a) the population inertia model, which holds that competition weakens with the age of the population (Hannan, 1997); (b) the trial-by-fire model, which considers that the effect on the possibility of failure of the density at the moment of foundation is positive, but this possibility of failure declines with the age of the organisation (Swaminathan, 1996); (c) the competitive intensity model, which contemplates the effects of the age and size of each organisation on the competitive environment experienced in the population (Barnett, 1997) and (d) the scale-based selection model, which considers the size as indicative of the firm’s strategy and its impact on the competitive environment (Dobrev and Carroll, 2003). From another point of view, the models of the second group are direct competition models. These models try to consider the effects of the direct competition between organisations by introducing connotations within the density variable, either from the size dimension (Hannan et al., 1990; Baum and Mezias, 1992; Wholey et al., 1992; Amburgey et al., 1994), or from other dimensions such as for example, geographic proximity (Carroll and Wade, 1991), strategic groups (Barnett, 1993), multi-market competition (Baum and Korn, 1996), or the position in the same or a different organisational niche (Baum and Singh, 1994; Baum and Korn, 1996). This current work, starting from Núñez and Moyano’s (2004) classification, focuses on those models that consider the effects of size on competition: (1) mass-dependence model (Barnett and Amburgey, 1990); (2) competitive intensity model (Barnett, 1997) and (3) scale-based selection model (Dobrev and Carroll, 2003).
2.1 Mass-dependence model Until the appearance of this model, researchers considered that the number of firms in a population (density) was an adequate approximation of the intensity of competition in a particular population (Hannan, 1989). Some empirical evidence demonstrates the validity of the density-dependence model (see Núñez and Moyano, 2004). Despite this, it is difficult for the model to describe the competition existing within a population precisely. Indeed, this model assumes that all organisations generate identical competitive pressure, regardless of their size. To get round this problem, Barnett and Amburgey (1990) introduce the influence of organisational size on survival, in an attempt to resolve the problems posed at that time: (1) do large organisations generate a strong competition? and (2) does the competition depend on the number of organisations? or on the aggregate size of the organisations? Until Barnett and Amburgey’s (1990) work, the literature did not provide a clear response to these questions. On the one hand, some researchers claimed to find that large firms generate a strong competition, while others claimed to find the opposite. And on the other hand, the density-dependence model only considers the number of firms existing in a population (density) to measure the competition, and not the organisations’ size. Various arguments support the idea that large organisations are strong competitors:
Size-competitive strength matrix for classifying organisations 1
In terms of direct competition, large companies’ strength is felt, in a market context, in price rivalry (Edwards, 1955). Large companies, at some time, exploit scale economies in production, achieving price levels that small firms cannot match. Furthermore, large organisations can withstand periods of low demand, and so they can use predatory pricing tactics to destroy small ones. But from the point of view of organisational ecology, the market context, of economic rivalry in prices, is only one example of the situations in which large organisations can be particularly competitive compared to their direct competitors. For example, large organisations frequently outcompete small organisations by achieving a higher quality in their services (Aldrich and Auster, 1986).
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In terms of diffuse competition, an organisation can reduce the viability of others that depend on the same source of resources (Hannan and Freeman, 1989). Large companies can exploit greater quantities of resources (financial, human, productive, etc.) than small ones. In this line, an organisation that is growing in size reduces the amount of resources available to other organisations whose chances of survival will therefore be undermined.
On the other hand, some arguments justify the survival of large organisations for reasons other than their stronger competitiveness. A powerful argument lies in the fact that the nature of the competition depends not only on the characteristics of the competing organisations, but also on the technical and institutional characteristics of the environment (Hannan and Freeman, 1977). Thus, it is conceivable that the dominant position of large organisations may favour mechanisms of institutional and technological support (e.g. subsidies, regulations, better access and handling of information) that cushion such organisations from selection pressures, thereby enhancing their survival prospects. In order to provide an empirical response to the above questions, Barnett and Amburgey (1990) develop a model illustrating the importance of size in competitive dynamics. This model uses as an explanatory variable of survival the aggregate size of all the members of a population (population mass). This model, known as the ‘mass-dependence’ model, postulates that an increase in this variable will increase the competitive intensity within the population, reducing firms’ chances of survival. However, these authors fail to validate the theoretical postulates of their model, since their empirical results suggest that large organisations do not generate greater competition, but in fact increase the viability of other organisations. This implies a curious symbiotic effect. On the one hand, some large organisations may establish good agreements with small collaborating organisations capable of undertaking certain activities more economically than they can. On the other hand, by associating with a large firm, a small organisation can expand its customer base, and in some cases gain access to regional or national networks (Fischer, 1987). Moreover, a large organisation can strengthen a small one, if this strengthening provides the small firm with shelter from its competitors. In this way, when large and small organisations work together, the strengths that could have made the large firm dangerous convert this large firm into a valuable ally instead. But evidence is not limited to collaboration or direct mutuality between pairs of organisations. This model’s estimations show that when an organisation grows in size it improves the viability of other organisations. Thus, large organisations also generate a diffuse mutualism, improving the viability of geographically-dispersed organisations (Barnett and Amburgey, 1990).
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara
2.2 Competitive intensity model Barnett (1997) continues to investigate the influence of size on vital rates, suggesting that selection works differently in small and large organisations, by virtue of two concepts: (a) the viability (understood as a particular organisation’s chances of survival) and (b) the competitive intensity (understood as the effects that an organisation’s actions have on other organisations’ chances of survival). Barnett (1997) develops a competitive dynamics model that attempts to overcome the limitations of previous models based on the density. The proposed model is known as the ‘competitive intensity model’, and assumes that the relation between competition and survival can be qualified, by considering other variables that can modify the behaviour of the explanatory variable defined on the basis of the population density (Núñez and Moyano, 2004). Specifically, the model captures the influence of each organisation’s characteristics on the competitive pressure by using the product of the age and size of each organisation. The main finding of Barnett’s study is that competition is extraordinarily different between organisations depending on the idiosyncrasies of each one, and that over time, small organisations generally compete more strongly, and large organisations generally compete more weakly. The author also provides theoretical arguments that explain how learning, experience and selection intervene in the evolution of small and large organisations (Barnett, 1997). Organisations evolve according to Barnett (1997) in the following way: 1
In small organisations, viability and competitive intensity are present jointly, as their viability is almost exclusively conditioned on competitive events. The smallest organisations are passive subjects of selection pressures. Their evolution develops according to the baseline model, which assumes that organisations acquire their adaptability at foundation, and this adaptability remains practically unchanged over time in the individual organisations. At the same time, firms face an adaptability threshold. Organisations positioned above the threshold have a greater chance of surviving than those positioned below it. Environmental selection allows the strongest organisations to survive (viability combined with competitive intensity). This is known as the ‘strong-survivor hypothesis’, which indicates that the oldest organisations have the greatest chances of survival (Barnett, 1997).
2
When organisations become large, they acquire the ability to control selection pressures, no longer remaining passive subjects of environmental pressures. Hence viability and competitive intensity diverge. Size provides advantages in competitive events, through the combination of capabilities (complementarity), reduction in costs or economies of scale, increasing organisations’ chances of survival, or in other words, their viability. But large organisations also experience non-competitive events that increase their viability: from the technical environment (technical and administrative functions) and from the institutional environment (large organisations obtain greater legitimation, wealth and power). Large organisations possess complex structures with a variety of units, while small organisations have simple structures and one or a small number of units. Selection permits that in large organisations, strong and effective units take weak and ineffective units along for the ride. This makes these large organisations less competitive than the survivors from a population of small organisations, whose units have all been selected and are consequently effective. Institutional legitimation benefits large organisations that
Size-competitive strength matrix for classifying organisations are favoured by other powerful institutions, receiving the benefits of governmental and professional regulations, access to capital, production factors and markets (DiMaggio and Powell, 1983). Large organisations gain power through the connection between networks of social influence, and possess considerable social status (Podolny, 1993). This set of characteristics that allows large organisations to survive even when they are weak competitors is termed compensatory fitness. Consequently, large organisations, in an evolutionary process, can guarantee their survival even if they are weak competitors, due to their compensatory fitness. This effect is known as the weak-survivor hypothesis. Figure 1 illustrates the postulates of the competitive intensity model. Figure 1
Different evolutionary mechanisms in small and large organisations according to the competitive intensity model COMPETITIVE EVENTS COMPETITIVE INTENSITY
NON-COMPETITIVE EVENTS TECHNOLOGICAL & INSTITUTIONAL ENVIRONMENTS (Compensatory fitness)
VIABILITY (1) Passive subjects of selection pressures
COMPETITIVE EVENTS COMPETITIVE INTENSITY (Delayed in relation to small organisations)
VIABILITY (2) Able to control selection pressures
Evolution develops according to the baseline model ‘Strong-survivor hypothesis’ Old, small and strong: High survival likelihood
SMALL ORGANISATIONS
‘Weak-survivor hypothesis’ Large and weak competitors. High survival likelihood due to compensatory fitness
LARGE ORGANISATIONS
VIABILITY (1) < VIABILITY (2)
Source: Own work based on Barnett (1997)
2.3 Scale-based selection model The models described above consider the effects of size on competition between the organisations of a population from a purely ecological perspective, analysing the effects of size on competition and of competition on the population’s birth/death rates, without taking into account organisations’ individual strategies. To get over this deficiency, Dobrev and Carroll (2003) develop a model which usefully draws together the ecological perspective and industrial organisation theory, and more specifically, strategic
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara management. These authors use the size variable to represent the strategy followed by the firm, which may be indicative of the relation between competition and survival. This approach is appropriate, because competition and strategy are strongly connected, and furthermore, organisational size is a powerful indicator of the strategic variation between organisations in the same sector. Dobrev and Carroll (2003) criticise Hannan and Freeman’s (1977) hypothesis that strong competition only arises in tightly packed regions of the size dimension. They think that it is necessary to distinguish between the absolute and relative effects of size (Dobrev and Carroll, 2003). Organisations may be at an advantage or disadvantage because of their large or small absolute size. Thus, strategic management postulates the beneficial effects to be gained when firms compete on production scale, when large size is a requirement, mainly due to the reduction in mean unit costs that is a consequence of raising production volumes. But among large firms that compete on scale, in turn, Dobrev and Carroll (2003) consider relatively large and relatively small firms, by comparing their positions on a size distribution. From these ideas, Dobrev and Carroll (2003) develop a model known as the ‘scale-based selection model’, on the basis of two hypotheses: (1) in a population that experiences both scale-based selection advantages and specialisation advantages, very large and very small organisations in relative terms are associated with low mortality rates and (2) in sectors where scale economies are important, the greater the size difference between an organisation and larger competitors, the greater the chance that it will fail. The first hypothesis assumes that very large organisations (relatively speaking) compete on scale, and very small organisations (relatively speaking) compete by specialising, coinciding with Porter (1980). Confirmation of this hypothesis is in line with Barnett and Amburgey’s (1990) findings, according to which large organisations are weak competitors and increase other organisations’ viability. These results assume that relatively small organisations benefit from large organisations by exploiting specialisation advantages in activities that are necessary for the larger organisations. In the second hypothesis, competitive pressure is established between the organisations of the population that compete exclusively on scale. The model postulates that the aggregate distance of a firm from its larger competitors measures the competitive intensity. The model also indicates that the positional advantages associated with size provide substantial benefits (social, political and economic) in the competitive process (Dobrev and Carroll, 2003). The model also assumes Barnett’s (1997) findings, according to which large firms (in this case, relatively large firm) are weak competitors and small firms (in this case, relatively small firms) are strong competitors. Although small competitors are stronger, their viability is lower, according to the weak-survivor hypothesis, which Barnett (1997) confirms, which also strengthens large firms’ evolution mechanism. Figure 2 summarises Dobrev and Carroll’s (2003) main findings. Size and competitive strength appear as variables on the x-axis and y-axis respectively. The inverse quadratic root of the size measures competitive strength (Dobrev and Carroll, 2003). In the large competitors’ zone, from a minimum size (Smin) organisations compete on cost leadership, exploiting the advantages of production scale, and the smaller firms by
Size-competitive strength matrix for classifying organisations differentiating, or even specialising. It is the relatively small or relatively large firms that have the best chance of surviving. Among those competing on production scale, those that are very far from the large organisations on the size distribution are most likely to fail. Figure 2
Importance of relative size on scale-based selection model Smin
COMPETITIVE INTENSITY –1/4 (SIZE) Competition on scale
Competition on specialisation + Probability of failure
Differentiation or specialisation
Cost leadership
+ Survival Likelihood + Failure likelihood + Survival likelihood
RELATIVELY SMALL
SMALL ORGANISATIONS
RELATIVELY LARGE
LARGE ORGANISATIONS SIZE
Source: Own work based on Dobrev and Carroll (2003)
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Theoretical interrelations between size, competition and survival
The analysed models describe the complex interrelationships between size and competition, as Table 1 shows. On the one hand, the scale-based selection model stresses the importance of relative size to competence while comparing the firm’s position in relation to the distribution of sizes within the population. This means that in a population made up of small firms it is possible to distinguish between relatively small organisations and relatively large ones. The same situation occurs in a population made up of large organisations; it is possible to distinguish between organisations of a relatively small size and organisations of a relatively large size. On the other hand, the competitive intensity model (Barnett, 1997) states that competition within the population depends on the evolutionary mechanisms that affect firms according to their size. Thus, in populations made up of small organisations, relatively small firms (according to the strong survivor hypothesis) will profit from a higher competitive strength as they manage to increase their size. In other words, small organisations of a relatively small size will be competitively weak while organisations of a relatively large size will be competitively strong. According to the strong survivor hypothesis, competitive strength diminishes as size increases in populations made up of large organisations. In other words, large organisations of a relatively small size will be strong competitors, while large organisations of a relatively large size will be weak competitors. Figure 3 shows a classification of organisations according to their absolute and relative sizes and the way they compete, which is also associated to organisational size.
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara Table 1
Interrelations between size and competition from organisational ecology
Model
Authors
Findings
Mass-dependence model
Barnett and Amburgey (1990)
•
Large organisations do not generate greater competition.
•
But in fact increase the viability of other organisations.
•
Competition is extraordinarily different between organisations depending on the idiosyncrasies of each one.
•
Over time, small organisations generally compete more strongly, and large organisations generally compete more weakly.
•
For small organisations, the ‘strong-survivor hypothesis’ is valid.
•
For large organisations, the ‘weak-survivor hypothesis’ is valid.
•
It is necessary to distinguish between the absolute and relative effects of size.
•
In a population that experiences both scale-based selection advantages and specialisation advantages, very large and very small organisations are associated with low mortality rates.
•
In sectors where scale economies are important (large organisations), relatively small organisations have higher mortality rates than relatively large ones.
Competitive intensity model
Scale-based selection model
Figure 3
Barnett (1997)
Dobrev and Carroll (2003)
Relative size and associated competitive strength
Source: The authors and Dobrev and Carroll (2003) and Barnett (1997)
Size-competitive strength matrix for classifying organisations Taking into account the organisational types identified in Figure 3 together with the effect that absolute and relative size exert on survival likelihood (Barnett and Amburgey, 1990; Barnett, 1997; Dobrev and Carroll, 2003), it is possible to suggest a set of propositions. By means of these propositions, it is also possible to draw up a pairwise comparison about survival likelihood associated to a specific organisation in relation to any other firm. Figure 4 shows the links that give rise to each proposition. Figure 4
Relative size, competitive strength and survival
Source: The authors
In a population made up of small firms, viability is closely related to competitive events. Therefore, according to the strong survivor hypothesis (Barnett, 1997), small organisations of relatively small size, given that they are weak competitors, will give in during their competitive struggle against small but relatively larger organisations. Drawing upon this rationale it is possible to argue that: Proposition 1: In a population of small organisations, competitively weak organisations of a relatively small size will be associated with lower survival rates than competitively strong organisations of a relatively large size. In a population made up of large organisations, relatively large organisations, in spite of being weaker competitors than relatively small organisations (Barnet and Amburgey, 1990), profit from a higher likelihood of survival. This effect can be explained because relatively large organisations can take advantage of their large size to build up compensatory adaptability (Barnett, 1997; Dobrev and Carroll, 2003): Proposition 2: In a population of large organisations, competitively strong organisations of a relatively small size will be associated with lower survival rates than competitively weak organisations of a relatively large size.
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara In a population with small and large organisations, taking into account relative sizes (Dobrev and Carroll, 2003), the selection mechanism that arises between small firms of a relatively small size, which are weak competitors, and large firms of a relatively small size, which are strong competitors, would be very similar to the mechanism that has already been described for small organisations or strong survivor hypothesis (Barnett, 1997). Therefore, Proposition 3: In a population made up of small and large organisations, competitively weak, small organisations of a relatively small size, will be associated with lower survival rates than competitively strong, large organisations of a relatively small size. Using the same rationale which gave rise to Proposition 3, in a population made up of small and large organisations and taking into account relative sizes (Dobrev and Carroll, 2003), the selection mechanism between competitively strong, small organisations of a relatively large size and competitively weak, large organisations of a relatively large size will be similar to the mechanisms that have already been described for large organisations (weak survivor hypothesis; Barnett, 1997): Proposition 4: In a population made up of small and large organisations, competitively strong, small organisations of a relatively large size will be associated with lower survival rates to a greater extent than competitively weak, large organisations of a relatively large size. In a population where small and large organisations interact, competitive events affecting small organisations of a relatively large size and large organisations of a relatively small size, where both are competitively strong, will benefit large organisations. This is because larger organisations will profit from being the largest competitors (i.e. compensatory adaptability and preferential relationships with public administrations). This rationale leads to the following proposition: Proposition 5: In a population with small and large organisations, all of which are competitively strong, small organisations of a relatively large size will be associated with lower survival rates to a greater extent than competitively strong, large organisations of a relatively small size. Nevertheless, the most surprising effect arising while analysing the relationship between size and competition consists of large organisations increasing other organisations’ viability (Barnett and Amburgey, 1990). As Dobrev and Carroll (2003) pointed out for a population made up of large and small organisations, the largest and the smallest organisations will be associated with low mortality rates. Thus, small, weak organisations of a relatively small size will benefit from a symbiotic relationship with large organisations. This is because these small and weak organisations are able to focus on activities aimed at satisfying the needs of weak and large organisations of a relatively large size (Proposition 6): Proposition 6: In a population with small and large organisations, all of which are competitively weak, small organisations of a relatively small size will show higher survival rates than competitively weak, large organisations of a relatively large size.
Size-competitive strength matrix for classifying organisations
4
Size-competitive strength matrix
On the basis of the propositions discussed above, this work proposes a matrix to characterise organisation types, following the same reasoning behind the Boston Consulting Group’s growth-market share matrix, which classifies products. This matrix compares organisations to marine species on the basis of the competition and size variables. The variable size adopts the values small and large, while competition adopts the values strong or weak. Each cell in the matrix contains a marine species that represents the competitive and size characteristics of the different types of organisation, and also the survival effects of some types of organisation on others. Drawing upon the propositions of the previous section, ‘whale’ organisations are very large but competitively weak organisations. ‘Sharks’ are also large organisations, but of a less size and competitively strong. ‘Moray eels’ are small organisations, relatively large and competitively strong. Lastly, ‘suckerfish’ organisations are relatively small and competitively weak organisations which profit from higher survival chances in relation to ‘whales’. Figure 5
Size-competitive strength matrix
SIZE Relatively small
Relatively large
SMALL
STRONG
LARGE
MORAY EEL
SHARK
SUCKERFISH
WHALE
COMPETITIVE STRENGTH WEAK
Relatively small
Relatively large
Source: The authors
The description of each of the organisation types participating in the size-competitive strength matrix is the following: Whale: These are organisations that are very large, weak competitors, but they have a high probability of survival due to the advantages of their size, according to the weak-survivor hypothesis (Barnett, 1997). They compete with similarly-sized organisations to capture resources, and they are unlikely to compete against smaller companies. Their large size makes them move slowly (strong structural inertia). These organisations may favour the survival of other, smaller organisations that benefit from staying close to them (suckerfish) and that use specialisation as a strategy. Whales rarely attack.
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara Shark: These are large organisations, but relatively smaller than whales. They are more competitive than whales, more agile and move more quickly. The benefits of size are not as acute, but since they are relatively small and strong competitors they are great survivors. Similarly to what occurs in nature, shark organisations do not live as long as whale firms. Sharks frequently attack. Moray eel: These are strongly competitive organisations. They survive over time thanks to their competitive strength (according to the strong-survivor hypothesis). They are specialist organisations, like the moray eel in nature, which specialises in hunting at night – hiding in cavities and cracks, in wait for its prey. Moray eels move quickly and with agility, and attack when they feel threatened. Suckerfish: These are small and weak organisations, with a poor chance of survival (strong-survivor hypothesis). They tend to survive close to large organisations, benefiting from their specialisation in a segment of the market, and protected from other competitors by these organisations, similarly to suckerfish (or remoras) in nature, which use their sucking dishes to attach themselves to whales. Each of the cells in the matrix reflects the results of the works analysed and also the relationships established in the propositions. The organisation characterised as a ‘whale’ is a large organisation, both absolutely and relatively (Dobrev and Carroll, 2003), and comparatively weak (Barnett and Amburgey, 1990). But it is also a large, old and weak organisation that survives in spite of its weakness because of the benefits of its size, in line with the weak-survivor hypothesis (Barnett, 1997). At the same time it favours the survival of other smaller organisations (Barnett and Amburgey, 1990), which benefit from their specialist relationship with the largest (Dobrev and Carroll, 2003; Barnett and Amburgey, 1990). The organisation characterized as a ‘shark’ is a relatively large organisation (Dobrev and Carroll, 2003), competitively stronger than other larger firms (Barnett and Amburgey, 1990; Barnett, 1997; Dobrev and Carroll, 2003). The organisation characterised as a ‘moray eel’ is a small organisation, but relatively large (Dobrev and Carroll, 2003), a strong competitor as well as a strong survivor (Barnett, 1997), with a specialist activity (Barnett and Amburgey, 1990; Dobrev and Carroll, 2003). Finally, the organisation characterised as a ‘suckerfish’ is a small organisation, both absolutely and relatively (Dobrev and Carroll, 2003), a weak competitor with little chance of surviving, according to the strong-survivor hypothesis (Barnett, 1997). But it benefits from its relationship with large organisations (Barnett and Amburgey, 1990), specialising in a very specific market segment in its relationship with these large organisations.
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Classification of organisations using size-competitive strength matrix
In order for the size-competitive strength matrix in this presentation to be useful in business management, managers need to be able to identify clearly where a particular organisation is located in the matrix. For this purpose, this section develops a methodology in the light of the models reviewed above that permits this identification.
Size-competitive strength matrix for classifying organisations With regards the size, a commonly used criterion to measure this variable is the number of employees (Segarra and Callejón, 2002). At the European level, the statistics offices of each country, together with EUROSTAT, classify firms in four intervals according to the number of workers: under 10; 10–19; 20–99; and over 100 workers. Following this classification, the threshold between small and large companies is 100 workers in our matrix. The number of workers may be an adequate measure for small firms, but it is less appropriate for large organisations, which may have significantly lightened their structures by subcontracting activities to smaller firms. Dobrev and Carroll (2003) consider a measurement of the size of large firms competing on scale from the demand side, taking the number of units produced by automobile manufacturers. A more general measure, also from the demand side, is the firm’s annual scale of operations. Just as two different mechanisms explain how selection operates in small and large firms (Barnett, 1997), this paper proposes two different measures for the variable size: the number of employees for the cells on the left of the matrix, and the revenue for the cells on the right (Figure 4). Notwithstanding this, the number of employees is the variable to distinguish between large and small firms. With regard to the competition, and following the same criterion, it is possible to propose two different measures for large and small firms. If the firm possesses a size associated with fewer than 100 employees, then it is located on the left-hand side of the matrix. Competition for the cells on the left is measured as in the competitive intensity model, that is, by the product of age and size (Barnett, 1997). Firms with over 100 employees are located on the right-hand side of the matrix. Then, the revenue measures the size from the demand side (Dobrev and Carroll, 2003). The competitive intensity is calculated as the inverse quadratic root of the size, similarly to in Dobrev and Carroll (2003). In Figure 6, the minimum and maximum values are at the extremes of the matrix. To fix these points, the SABI (Sistema de Análisis de Balances Ibéricos, Iberian Balance Sheet Analysis System) database (Informa, S.A.) collects economic-financial information from the Spanish firms obliged to register their accounts at the Registry of Companies. Thus, the maximum size corresponds to the organisation occupying first place in terms of revenue (€30 billion). The revenue at the dividing line corresponding to firms of 100 employees adds up the mean revenue of firms with a similar size to this level – €14 million. With regard to the measure of competitive strength, in the case of large firms the maximum value is determined by the revenue corresponding to 100 employees subjected to the formula (revenue)-1/4. For smaller firms, the reasoning of studies using the combined effect of firm age and size is useful to estimate the competitive dynamics of the population (Ranger-Moore, 1997; Hannan et al., 1998). Thus, and using the SABI database, the diagonal on the left-hand side of the matrix determines a mean age of 12 years for the Spanish firms with under 100 workers. Figure 7 also shows the logical movements that firms can conceivably make throughout their lifetimes between the cells of the matrix. These are indicated with clear grey arrows. Atypical movements can also occur, but these are not illustrated.
Soruce:
WEAK
Age x Size
STRONG
The authors
0
600
1
SMALL
50
2
100 Number of employees
SUCKERFISH
Specialisation strategy
MORAY EEL
Differentiation or specialisation strategy
3
Cost leadership strategy
LARGE
Revenue
WHALE
4
SHARK
Specialisation or differentiation strategy
225,7 M €
Danger zone
14 M €
0.258
(Revenue)–1/4
0,517 0.517
SIZE
Maximum size
5
Figure 6
1.200 1,200
COMPETITIVE STRENGTH
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara Classification of firms according to the size-competitive strength matrix
Size-competitive strength matrix for classifying organisations Figure 7
Flow diagram for firm classification according to the size-competitive strength matrix
Source: The authors
6
Strategic implications of size-competitive strength matrix for management
Determining in which cell a particular organisation is located is, on the one hand, a measure of the interaction between size and competition. On the other hand, it is a useful tool for taking future decisions. Some of the implications underlying the logical movements between matrix cells are in Figure 6. ‘Suckerfish’ organisations tend to be either younger or older firms that prefer to remain small and continue to benefit from their comfortable, risk-free position. The organisations situated in the ‘suckerfish’ cell may manipulate their size to move over to the ‘moray eel’ cell. This change of cell implies passing from specialisation in an activity for a large organisation to extending products and services to more customer segments and/or increasing the number of large suppliers on which the firm depends. Vertical integration movements between small ‘suckerfish’ can extend their field of action and
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara shift them towards the ‘moray eel’ cell. Associative movements or alliances between ‘suckerfish’ may also prove useful. A ‘suckerfish’ firm that is located near the dividing line with ‘moray eels’ must decide whether to increase in size – thereby losing the benefits it obtains from the large ‘whales’ – or to control its size and remain in the shadow of the larger organisation. If it decides to change cells, internal growth may be the appropriate formula. ‘Moray eel’ organisations can shift towards ‘shark’ organisations if they increase their size by taking on more employees. Small ‘moray eel’ organisations must merge to attain sufficient size to become ‘sharks’. Larger ‘moray eels’ can acquire small ‘suckerfish’ to reach an adequate size. In this respect, horizontal integration movements may be effective. From a minimum size on, ‘shark’ firms radically expand their field of activities. Outsourcing may be useful to attend to the new customer segments. It will sometimes be necessary to attend to particular market segments with low margins, if these provide sufficient revenue. This position corresponds to a turbulent environment (complex, dynamic and full of uncertainty), where the competition is very intense. ‘Shark’ organisations can reduce their number of employees by downsising, but they may maintain their ‘shark’ position by virtue of their high revenue. Organisational phenomena such as alliances, networks or virtual organisations may contribute to this situation, encouraging ‘shark’ firms with a higher revenue to concentrate on their core activities. ‘Sharks’ may recede to ‘moray eels’, thereby fleeing an uncomfortably dynamic position. Abandoning certain unprofitable market segments can help these organisations to maintain an acceptable profit level despite having reduced their revenue. In the change, the firm must take care to keep the appropriate number of employees. Finally, the shift from ‘shark’ firms to large ‘whales’ is extremely risky. A significant increase in size is essential to avoid the danger zone. Furthermore, the movement also implies a change in the firm’s strategy, which will become cost leadership. The increase in size should imply an important increase in the revenue, or alternatively an increase in resources permitting the investments required to change the strategy. Listing on the Stock Exchange could be an appropriate way of achieving these resources. Mergers between various ‘sharks’, ‘moray eels’ and ‘suckerfish’ may sometimes provide sufficient resources and size for this change to become possible. Spain has recently experienced an example of firms that may well have obtained the advantages of ‘whales’ without giving up their ‘shark’ condition. For example, the following IT-sector firms: (a) Ingenia; (b) Novasoft; (c) Guadaltel; (d) Agresso and (e) the recently-created MLK Tecnología. The resulting firm, Islanda (Innovation in Open-Source Software, Applications Analysis and Development), immediately becomes one of the major services companies in the Spanish IT sector. In turn, ‘whale’ organisations attempt to continue growing in size in terms of revenue and reduce their costs, in order to distance themselves from the danger zone. Again, horizontal or vertical integration strategies are valid as long as the unit costs do not rise, such as in network or virtual organisation configurations strategies. Turning back from the ‘whale’ position to the ‘shark’ position would be extremely complex. Reducing the revenue would imply changing the organisation’s competitive attitude, but slow ‘whales’ are not ideally placed to do this. Failure in this position tends to end in the death of the organisation. When this happens, the large, ailing ‘whale’ sometimes breaks up into a number of small organisations that inherit some of the benefits of their ancestor.
Size-competitive strength matrix for classifying organisations Over time, some strange movements may arise transforming a ‘suckerfish’ into a ‘whale’, passing through the various cells of the matrix. An example of this is the firm AMD, which goes from being a ‘suckerfish’ that manufactures microprocessors for Intel to being, at present, a ‘whale’ firm that is Intel’s main competitor. Another curious and atypical example of rapid shifts between cells occurred in Spain, with the firm Terra, a subsidiary of the telecoms firm Telefónica. Terra was born as a ‘shark’ specialising in internet services through a general-purpose portal. The firm started from the acquisition of the internet portal Olé, a small firm that had the initial support of the public administrations, and which could consequently be classified as a ‘suckerfish’. An early listing on the Stock Exchange provided Terra with sufficient resources to grow strongly and became a ‘whale’, passing over the danger zone. Subsequently, Terra merged with Lycos to increase in size further and distance itself from the danger zone. Today, after the bursting of the technology bubble in the spring of 2000, and the loss of resources as a consequence of the collapse in its share price, it would be very difficult for the firm to return to its initial position as a ‘shark’. It may be that its chances of survival are dependent on it moving cells to become a ‘suckerfish’, with its activity linked to its parent firm Telefónica, or even on it being integrated into that firm as its internet division.
7
Conclusions
This work offers a new strategic tool for classifying organisations on the basis of the interrelations between size and competition. For this purpose, the first aim of this work is to carry out a review of the different models that consider the effects of competition on the vital rates of organisational populations from the organisational ecology perspective, focusing on those models that consider the size variable. These models show theoretical interrelations among size, competition and survival chances in several organisations. On this basis, the proposed size-competitive strength matrix classifies organisations into four groups: (1) ‘suckerfish’: small, competitively-weak organisations whose survival benefits symbiotically from large organisations that are also competitively weak; (2) ‘moray eels’: small organisations, but relatively large, which are strong competitors and compete by specialising; (3) ‘sharks’: large, competitively-strong organisations, which are extremely agile and expand their scope of specialisation extending their segments of activity and (4) ‘whales’: large, competitively-weak organisations, which are engaged in scale competition, using a cost leadership strategy. The second aim is to design a method for locating organisations in a particular cell of the size-competitive strength matrix. This localisation may guide professionals involved in decision-making about how to manipulate their organisation’s size to move between the cells of the matrix, with all the implications and repercussions that this decision will have for the organisation’s competitive strength. This work has a number of limitations. First, it is a theoretical work, and it consequently suffers from the typical limitations of this type of study. It is necessary further empirical research to test and extend the relations proposed here. Researchers could for example examine the relationship between the position in the matrix of a series of organisations in a particular population and the competitive advantage obtained by each of them, measuring the influence of alternative strategies, such as differentiation, cost leadership, growth, alliances or innovation. Second, the sector or industry in
J.M. Maqueira-Marín, J. Moyano-Fuentes and S. Bruque-Cámara which the organisation operates may be a determinant variable for carrying out the characterisation, since some typologies may not be present in some industries. Future research could subject the size-competitive strength matrix to comparative multi-sector studies to investigate the differences that may exist between sectors, expanding the range of implications for management in each of the sectors analysed. Finally, the measures used here to delimit the cells in the matrix are necessarily subject to error, since the literature has yet to reach a clear consensus about how to differentiate between small, medium-sized and large firms.
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Note 1
This study was funded by the research project SEJ2006-04777 of the Spanish Ministry of Science and Education.
