Does the Environment Influence the Employment Growth SMES

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Journal of Small Business and Entrepreneurship 22, no. 3 (2009): pp. 311326 311

Does the Environment Influence the Employment

Growth of SMEs?

Frank Janssen, Holder of the Brederode Chair in Entrepreneurship,

Universit catholique de Louvain, 1, Place des Doyens, 1348 Louvain-

la-Neuve, Belgium

ABSTRACT: A great deal of empirical research has been devoted to the study of the impact of a

firms environmental characteristics on its growth. However, most of this work focused on one or a

few predictors. Furthermore, no research has provided an exhaustive list of all variables previously

studied. We have tried to fill this gap and have tested on a sample of Belgian SMEs the potential

influence of 15 variables on employment growth. On the basis of Mintzbergs classification, wehave grouped our variables into three sub-categories of determinants relating to the generosity or

hostility of the environment, to its stability or dynamism and to its simplicity or complexity. Our

results show that employment growth within SMEs is only influenced by two variables linked to the

generosity sub-group. These also show that the environment, at least if it is studied independently,

has only an extremely limited influence on the growth of SMEs. This leads us to question the valid-

ity of purely external approaches to firms employment growth, such as the theory of population

ecology of organizations.

Rsum : De nombreuses recherches empiriques ont port sur limpact des caractristiques environnementales

dune entreprise sur sa croissance. Cependant, ces tudes ne mettaient laccent que sur un ou quelques facteurs

prdictifs. De plus, ce jour, aucune recherche na fourni une liste exhaustive de toutes les variables qui ont t

tudies. Nous avons tent de combler ce manque et avons test auprs dun chantillon de PME belges limpact

potentiel de 15 variables sur la croissance de lemploi. La classification de Mintzberg fut utilise afin de

regrouper les variables en trois sous-catgories. De facteurs relatifs la gnrosit ou lhostilit de lenviron-

nement, sa stabilit ou son dynamisme, et sa simplicit ou sa complexit. Les rsultats rvlent que seulementdeux variables de la sous-catgorie gnrosit jouent un rle dans la croissance dune entreprise. Les

rsultats rvlent galement que lenvironnement dans lequel lentreprise volue, du moins lorsqutudi de

faon isole, ne joue quun rle trs limit dans la croissance des PME. Ces rsultats amnent les auteurs

questionner la validit des approches strictement externes, telles qui lcologie des populations.

Introduction

Since the publication of Birchs work in 1979, an impressive number of studies have been

devoted to the role of small and medium-sized enterprises (SMEs) in job creation. In a

book published in 1987, Birch observed that most employment was created by a tiny pro-

portion of companies (i.e. fast-growing companies). Several other studies from both

Europe and America confirm this phenomenon (OFarrell, 1984; Dunkelberg, William

and Cooper, 1982; Storey and Johnson, 1987; McMullan and Vesper, 1987; Gallagher and

Miller, 1991; OECD, 1999; Julien, 2000).

Growth has been measured on the basis of an impressive number of variables, but the

two indicators that are most widely used in literature are employment and sales. We

decided to limit the scope of this paper to employment growth. Apart from the fact that it

is a measure of economic growth (Kirchoff, 1991), it can serve as an indicator of the entre-

preneurs success and, for society as a whole, it represents a measure of the firms

JANSSEN.qxp 8/13/2009 1:33 PM Page 311


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economic contribution to the common good (Dunkelberg, William and Cooper, 1982).

That is why this criterion has been used by many economists and sociologists, even

though it seems that companies themselves prefer to measure their success in terms of

sales growth (Hughes, 1998; Donckels, 1990), and that the latter criterion has been

favoured by researchers in management sciences (Weinzimmer, 1993). Furthermore,according to Child (1973), employment is an appropriate criterion for measuring the size

of an organization, as it is primarily human beings that are organized. Finally, since

managers generally wait for demand to stabilize before recruiting personnel, employment

is, in theory, a less volatile measure of growth than sales (Delmar, 1997). In some

European countries, such as Belgium, the stability of this criterion is reinforced by rigidi-

ties on the labour market, linked to restrictive social legislation.1

Two competing theoretical approaches designed to explain the causes of performance

and growth have been developed in the field of management sciences (Weinzimmer,

1993). The first approach, which we can call the external model, studies the influence

of environment on organizations. The source of this external perspective goes back to the

industrial economy movement, the so-called structuralist movement, which postulates that

industrial structures determine the conduct of firms and hence their performance (Julien

and Marchesnay, 1997). According to this movement, the performance of a company

should tend towards that of the industry as a whole under the effect of competition. The

structuralist school has influenced the strategic thought movement referred to by

Mintzberg, Ahlstrand and Lampel (1999) as the environmental school, which came to the

fore primarily due to the work of population ecologists (Hannan and Freeman, 1977). This

school maintains that the conditions found in a companys external environment are the

principal determining factors in its survival. The second approach, in other words the

internal model, is chiefly concerned with studying the internal characteristics of a com-

pany and the way in which an organization adapts to its environment and attempts to

shape it. The initial source of this internal approach is to be found in the industrial organ-

ization movement, also known as the behaviorist approach and, ultimately, in strategic

management. The industrial organization movement believes that an industry is made up

of companies that not only pursue their own personal strategies, but also build up the basicstructures of the industry, along with other companies, by means of these strategic deci-

sions on matters such as investment, technology, markets and products (Julien and

Marchesnay, 1997). The resource-based theory (Barney, 1986; Wernerfelt, 1984) is con-

sistent with the internal approach movement. According to Lohmann (1998), studies that

are concerned with the impact of entrepreneurs own characteristics should come under

this theoretical movement. By the same token, it is possible to say that economic models

of human capital (Oi, 1983; Lucas, 1978) and entrepreneurial learning (Audretsch, 1994;

Jovanovic, 1982) may be regarded as an internal type of approach.

Growth is a complex and multidimensional phenomenon (Weinzimmer, 1993), so it goes

without saying that a purely external or internal type of approach will inevitably be over-

simplistic. However, within the limited context of this paper, we have decided to concentrate

on the external approach and specifically on the influence of environment-related factors on

growth.2 We are aware that this decision ignores the predictive potential of internal variables

312 JANSSEN

_________________________

1. Of course, it is possible to increase sales without recruiting additional employees (Delmar, 1999), for instance

through subcontracting. However, such a decision would have a positive impact on employment at the macro-

economic level.

2. For an analysis of a complete causal growth model, see Janssen (2002).



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linked to the manager (Janssen, 2006),3 the firm and its strategies, and does not take the

interactions between different types of variables into account (Janssen, 2002).

The analysis of the relationship between environmental characteristics and company

growth has already given rise to numerous empirical studies. However, the vast majority

of research on growth has only studied the impact of a limited number of variables.

Moreover, most of this work has a relatively weak theoretical basis. The concept of

growth is only rarely justified in theoretical terms. This area of research is highly frag-

mented, accentuated by the fact that too much attention is paid to the manufacturing sec-

tor, and that there is considerable variety in terms of the time period studied and of the

way in which growth is measured (Janssen, 2002). It is also regrettable that, with the

exception of Swedish and British scholars, few European researchers have taken any

interest in this issue.

Several authors (Grinyer, McKiernan and Yasai-Ardekani., 1988; Miller and Friesen,

1984) agree that the impact of a large number of variables needs to be tested simultane-

ously in order to arrive at a global and more realistic picture of the growth phenomenon.

To our knowledge, no research project to date has attempted to provide an exhaustive list

of all the independent variables examined by previous studies.Based on a state-of-the-art study of the research on environment-related growth deter-

minants, we formulate 15 hypotheses. These hypotheses use all the determining factors

that we have identified in the literature on growth. Rather than making value judgments

on the relative importance of particular variables, which would have left us with only a

limited number of hypotheses, we will test all these variables, as several recent empirical

studies have demonstrated the surprising importance of factors that may, at first sight,

seem to be of minor interest (e.g. see Gartner and Bhat, 2000).

Environmental Impact Hypotheses

From an economic point of view, the environment corresponds to a set of exogenous

determinants, i.e. pre-determined or set (Pearce, 1997). Mintzberg (1979) classified the

environmental aspects identified by research on the basis of four major characteristics:

generosity, dynamism, complexity and market integration.The environment can be generous or hostile. Generosity represents the extent to which

an environment is liable to stimulate sustained growth (Starbuck, 1976). A hostile environ-

ment, on the other hand, curbs growth. The environment may also be stable or dynamic.

Dynamism is related to the degree of instability of a market. Dynamism is the result of

unforeseen factors that it is not possible to plan for in advance, such as unpredictable

changes in demand or competition, or rapidly changing technology. These factors give rise

to uncertainty, which makes it more difficult for managers to process all the information

(Dess and Beard, 1984). Moreover, the environment may be simple or complex. Complexity

arises from the companys need to gather large quantities of information and facts about its

products or customers. If this knowledge can be rationalized, in other words, broken down

into sub-groups that are easy to grasp, the environment can be regarded as simple

(Mintzberg, Ahlstrand and Lampel, 1999). According to Child (1972), complexity is due to

the variety and range of activities carried out by an organization. Finally, a companys mar-kets may be integrated or diversified. This can also be expressed as homogeneity or seg-

mentability. According to Dess and Beard (1984), this aspect of the environment is

DOES THE ENVIRONMENT INFLUENCE THE EMPLOYMENT GROWTH OF SMES? 313

_________________________

3. In this other paper, published in the same journal, we concentrated on the impact of entrepreneurial variables

on employment growth.



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contained within the notion of complexity. Environmental aspects can therefore be reduced

to three categories: generosity, dynamism and complexity (Dess and Beard, 1984).

Generosity

Of all the environmental variables that influence growth and that have been considered by

empirical studies, generosity is by far the most widely examined. These studies have par-

ticularly looked at variables such as sectoral growth rate, level of concentration, entry bar-

riers, public aid, economic policies, degree of unionization, the crime rate and the appear-

ance of the area in which the company is located, the proximity of university institutions,

whether or not the company is based in a science or industrial park and the regional

economic environment.

As a general principle, industry growth means that existing companies do not neces-

sarily suffer if newcomers take a share of the market. This also reduces the likelihood of

retaliation by these existing companies (Porter, 1980). Theoretically, a growth market

offers more opportunities, especially for newcomers since, by definition, demand within

the market is growing (Eisenhardt and Schoonhoven, 1990). Weinzimmer (1993) notes the

existence of a positive relationship between the generosity of the environment and growth

in sales, assets and employment. According to this author, this would tend to demonstratethat the growth of a company could simply be due to the fact that it belongs to a gener-

ous sector. Such an environment would allow companies to grow without having to

acquire resources or market shares at the expense of their competitors. This positive effect

of industry growth is confirmed by Audretsch (1995) and Audretsch and Mahmood

(1994). Other studies highlight considerable sectoral differences in terms of firm growth

rates (Brush and Chaganti, 1999; Storey, 1994b; Siegel, Siegel and MacMillan, 1993;

Eisenhardt and Schoonhoven, 1990; Dunkelberg, William and Cooper, 1982).4 Medium or

high-tech sectors appear to have a higher percentage of fast-growing SMEs than other sec-

tors (Calvo and Lorenzo, 2001; Philips and Kirchoff, 1989). High-growth firms would

rather be found in growing sectors (Woywode and Lessat, 2001; Davidsson and Delmar,

2001). On the basis of theoretical arguments and empirical results, we would put forward

the hypothesis of a positive link:

H1: the sectoral growth rate has a positive influence on the firms growth.

A high rate of concentration and high entry barriers do, in principle, protect existing

firms from the arrival of newcomers and should therefore stimulate their growth

(Hamilton and Shergill, 1992). The intensity of competition restricts access to resources

for a recently established business or a newcomer (Romanelli, 1989). A considerable

degree of competition also implies lower prices and profit margins than in a more con-

centrated structure, which could have a negative effect on growth. However, less concen-

tration should, in theory, allow more companies to grow (Eisenhardt and Schoonhoven,

1990). An American study observes a positive link between the concentration rate of a

sector and growth in sales and employment (Weinzimmer, 1993). This is confirmed by

Geroski and Toker (1996). Along the same lines, a Swedish research notes that there is a

negative link between competition intensity and growth (Delmar, 1997).5 We also presup-

pose a positive influence:

314 JANSSEN

_________________________

4. A few studies have found no impact of sectoral growth rate on companies growth (Wiklund, 1999; Kalleberg

and Leicht, 1991).

5. Two other studies observe no significant link between these variables (Kalleberg and Leicht, 1991;

Einsenhardt and Schoonhoven, 1990).



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H2: the level of market concentration has a positive influence on growth.

Some researchers studied a specific aspect of concentration, i.e. the impact of entry

barriers on company growth. Entry barriers are said to exist when, in a given market, com-

panies are capable of maintaining monopolistic prices and profits without attracting new-

comers. These entry barriers may be linked to the capital intensity of a sector or to the pro-

motion or R&D expenditures of existing companies. The promotion expenditures of exist-

ing firms create expenditure thresholds below which promotion no longer has any impact

(Comanor, Kober and Smiley, 1981) and increases the loyalty of consumers to the exist-

ing firms (Scherer, 1980). In order to build up a reputation, a newcomer would have to

consider a disproportionately high outlay in order to attract consumers. Considerable

R&D expenditure can also be an entry barrier (Comanor, 1967). This actually increases

the initial outlay that newcomers have to make and increases the complexity of the knowl-

edge base they have to acquire. In certain industries, R&D is used as a defensive weapon

allowing companies to file patents that are not necessarily used. Companies that already

have a footing in the market in question should benefit from these entry barriers and grow

more rapidly than they would if these barriers did not exist. These barriers actually reduce

the numbers of newcomers or prevent their entry to the market and allow these firms tomake monopolistic profits. One study notes that there is a positive link between the scale

of the entry barriers resulting from R&D and promotion, on the one hand, and sales

growth (Weinzimmer, 1993). We formulate the same hypothesis for employment growth:

H3: the existence of entry barriers linked to capital intensity and R&D or promo-

tion expenditure has a positive influence on growth.

Governmental support ought to help stimulate growth. A study conducted in Quebec

reports that government subsidies, particularly in the R&D and export fields, have a pos-

itive effect on growth (Julien, 2000). Still on the subject of economic policies, high fiscal

pressure, restrictive social legislation or difficult industrial relations, which are generally

perceived as curbing growth, could have a negative effect on growth (Gibb and Davies,

1990). These variables do, as a general rule, correspond to hostile policies as far as busi-

nesses are concerned. We thus put forward the following hypotheses:

H4: obtaining public aid has a positive influence on growth.

H5: restrictive fiscal and social policies have a negative influence on growth.

The degree of unionization of the company or the sector to which the company

belongs is also liable to affect growth. Wooden and Hawke (2000) note that a majority of

Anglo-Saxon authors with an interest in the impact of unions on employment and growth

in employment feel that the degree of unionization generally has a negative effect for three

main reasons. First, salaries in highly unionized companies tend to be much higher than

in those that are not. As a result, these companies would employ fewer workers than a sim-

ilar company with less unionization. Second, the effect of unionization on productivity

would tend to be negative or fairly low. Third, unions tend to favour the salaries of their

members to the detriment of the employment situation. A fourth reason provides a possi-

ble explanation for this potentially negative link: unions seek to minimize opportunities

for reducing the workforce, which is in turn liable to discourage recruitment. Several

studies conducted in the United States, Canada, the United Kingdom and Australia

observe that the employment growth rate in unionized companies is two to four percent

lower than in non-unionized companies (Wooden and Hawke, 2000; Blanchflower and

Burgess, 1996; Long, 1993; Leonard, 1992). Other authors also note that the degree of




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unionization in a sector has a negative influence on the growth of SMEs (Acs and

Audretsch, 1990). Along the same lines, Grinyer, McKiernan and Yasai-Ardekani (1988)

report a negative relationship between the managers perception of pressure from the

unions and growth. However, this negative perception must be treated with caution. It may

equally well result from the managers need to justify low growth by putting it down toexogenous factors over which he/she has no control, as from real growth inhibitors such

as excessive pay demands, repeated production stoppages or a rigid and aggressive union

policy (Grinyer, McKiernan and Yasai-Ardekani, 1988). On the basis of theoretical argu-

ments and corroborative conclusions from empirical studies, we put forward the hypoth-

esis of a negative link:

H6: a high rate of unionization has a negative influence on growth.

The location of a company is also liable to influence growth, be this with regard to the

area itself, the immediate vicinity or the region in which it is situated.

As far as the immediate geographical environment of the company is concerned, a

study (Gartner and Bhat, 2000) reports that the crime rate in a particular area, as well as

its appearance in terms of upkeep and cleanliness of streets, pavements and buildings,

have a significant correlation (negative and positive, respectively) with the growth fore-casts of the company manager. These results confirm the results of other studies (Bull and

Winter, 1991).

H7: the crime rate in the area where the company is located has a negative influ-

ence on growth.

H8: the appearance of the area where the company is located has a positive influ-

ence on growth.

In addition, the proximity of university institutions is also liable to have a positive

effect on growth (Snuif and Zwart, 1994). This proximity allows companies easier access

to scientific expertise and to the results of certain research programs, thus making it eas-

ier to market these research results (Colombo and Delmastro, 2002). Similarly, the fact

that the company is based in a science or industrial park may also have a copycat effect

of stimulating growth. These parks may be defined as public and/or private property ini-tiatives that aim to promote the start-up and development of businesses by providing

logistical, technical, administrative and/or managerial services, technology transfer and

network development between the firms based in the park, as well as between these firms

and universities or public bodies. These parks allow businesses to benefit from agglom-

eration economies associated with interactions between companies that are concentrated

within a restricted space (Marshall, 1922). Unlike science parks, industrial parks focus

less on high-tech activities or activities that are associated with the use of scientific results

and are characterized by weaker or non-existent links with academic institutions or

research centres (Colombo and Delmastro, 2002). A British study (Westhead and Storey,

1994) shows that location in a science park has a positive effect on growth. These results

are confirmed by an Italian study that examines both science and industrial parks

(Colombo and Delmastro, 2002). We have formulated identical hypotheses:

H9: the proximity of university institutions has a positive influence on growth.

H10: the fact that the company is based in a science or industrial park has a pos-

itive influence on growth.

As far as the regional geographical environment is concerned, it is possible to make a

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distinction between rural and urban areas. In a rural area, the resources required for

growth, such as specialized production factors, may be harder to find than in an urban

area. For example, a rural area is more likely to have shortages of specialized or manage-

rial staff (OFarrell and Hitchens, 1988). The population density in an urban area also pro-

vides a larger potential demand than would be the case in a rural area (Woywode andLessat, 2001). On the basis of these arguments, we formulate the hypothesis that an urban

location has a positive effect:

H11: the fact that the company is located in an urban area has a positive influence

on growth.

Being located in a region that is considered more economically developed or more

dynamic than another region could also influence growth. The extent of development of

the means of communication within a region can have an impact on growth. In principle,

the more developed the road infrastructure, means of transport and communication net-

works, the greater the effect on growth. Macroeconomic conditions can also vary from

one region to another and some regions may experience lower economic growth rates

and/or lower income levels that might inhibit company growth (Gabe and Kraybill, 2002).

Some regions attract more economic activities than others. In addition, regions competewith one another to attract national or foreign investment. However, in Quebec, Julien et

al. (1997) do not observe any systematic influence on company growth associated with

being located in a particular region. On the basis of theoretical arguments, we put forward

the hypotheses of positive links:

H12: a sufficiently developed road infrastructure, means of transport and commu-

nication networks have a positive influence on growth.

H13: the dynamism of the region in which the company is located has a positive

influence on growth.

Dynamism and Complexity

Very few studies have examined the impact of the dynamism and complexity of environ-

ment on growth.

According to Weinzimmer (1993), dynamism, at least if it is the result of innovation,

could be a source of growth opportunities for companies that already have a hold in the

marketplace. In addition, growth makes it possible to reduce the uncertainties associated

with market dynamism. However, empirical studies have found no significant influence

of environmental dynamism on growth (Wiklund, 1999; Weinzimmer, 1993). However,

on the basis of the theoretical arguments, we will assume that the many market opportu-

nities available in a dynamic environment are likely to stimulate growth and, hence, that

a positive effect should prevail.

H14: the dynamism of the environment has a positive influence on growth, where

such dynamism is defined as a market that is experiencing rapidly changing

technology.

Some researchers have observed that a complex or unstable economic environment

and, in more specific terms, the perceived difficulty of predicting economic conditions,

has a negative impact on growth (Grinyer, McKiernan and Yasai-Ardekani, 1988). We can

assume that this complexity slows down the decision-making process. Based on this

empirical result, we put forward the hypothesis of a negative link:

H15: a complex environment has a negative influence on growth, where such an




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environment is defined as being the degree of complexity associated with collect-

ing data and/or facts regarding a firms products or customers, or the difficulty of

predicting economic conditions that affect the market.6

MethodologyPopulation, Sample and Representativeness

A database compiled by ING Bank (Internationale Nederlandse Groep) that includes all

firms established in Belgium that have delivered their annual accounts to the Accounts

Central of the Belgian National Bank was used in order to determine the population of

SMEs to be analyzed. We have retained all firms that were active over the period studied

(19942000) for which we have data on employment for 1994 and 2000 and which cor-

responded in 1994 to the definition of an SME given by the European Commission. 7

Insofar as numerous firms in Belgium have been created purely for fiscal reasons8 and do

not really undertake activities, we have eliminated firms that were already active in 1994,

but that still employed less than five people in 2000.

On the basis of these criteria, the population was composed of 11,481 firms. We ran-

domly selected 788 firms, while at the same time ensuring proportions of micro- (less than

10 people), small- (between 10 and 49 people) and medium-sized (between 50 and 249

people) firms identical to those of the total population. In order to allow a dynamic analy-

sis, this size criterion was checked at the beginning of the period studied, in 1994. We also

kept the proportions of firms from the three regions of the country (Flanders, Wallonia,

Brussels) identical to those of the population.

Out of the 788 firms, 331 refused to participate in the survey and 186 were not avail-

able during the interview period. For 121 other firms, the telephone number in the data-

base was incorrect or corresponded to a fax number. Our study therefore focused on a

sample of 150 firms. According to Harris (1985), the size of the sample must exceed the

number of predictors by at least 50. Our sample of 150 observations respects this rule.9

In order to determine the representativeness of our sample in relation to the original

318 JANSSEN

_________________________6. See Grinyer, McKierman and Yasai-Ardekani (1988).

7.According to the European Commissions Recommendation of April 3, 1996 (OJEC, L 107/4, 1996), the fol-

lowing firms must be considered as SMEs:

- those employing less than 250 people; the number of people employed corresponds to the number of annual

work units.

- those whose either turnover does not exceed 40 million EUR., or the annual balance sheet total does not exceed

27 million EUR.

- those that respect an independence criteria. Independent firms are those which are not owned as to 25% or

more of the capital or the voting rights by one or several large firms. We have not used this criterion, given

that one of our hypotheses presupposed that the fact that a firm is dependent on another firm would have a

positive influence on the growth of the former.

The Commission also distinguishes medium-, small- and micro-sized enterprises. The small firm is that which

employs less than 50 people. This respects the independence criterion defined above and for which either the

turnover does not exceed 7 million EUR, or the annual balance-sheet total does not exceed 5 million EUR. A

firm is considered to be micro-sized if it has less than 10 workers.

8. The fiscal regime for companies is in fact more advantageous than the regime for physical persons. As a resultmany people create empty firms only in order to deduce expenses. These empty shelves do, of course, not

grow.

9. According to other authors (Bernard, 1999), a minimum of 10 observations per predictor is necessary. Harris

(1985) underlines that this principle is not based on any empirical proof. Others suggest more liberal rules

than Harris and consider that the number of observations must only exceed the number of variables by 40 (see

Howell, 1998).



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population, we compared the average growth10 of the sample firms to the one of the pop-

ulation11 using a bilateral t-test. One of the application conditions underlying this test on

two independent samples is the homogeneity of variances (Howell, 1998). We first used

Levenes test to check that there is no significant difference in the variances (F= 1.476

and sign. = 0.224), and then tested the difference between the averages of employmentgrowth for the two groups. The results of the bilateral t-test (t= -0.823; d.f. = 11.479; sign.

= 0.411) indicate that the average employment growth of the firms in our sample is not

significantly different from that of the firms of the overall population.

As our sample was composed on the basis of size and regional location constraints

characteristic of the population, it is no longer necessary to examine the representative-

ness of the sample in relation to the population with regard to these two criteria. Finally,

we also examined the percentages of independent firms within the population and the

sample. These are also identical (66.7%). These particular elements of comparison were

chosen because they appear in the initial database.

Data Collection Method and Measure of the Dependent Variable

The data published by Belgian firms do not make it possible to test the vast majority of

the hypotheses developed in our research. Hence, we opted for a telephone survey. 12 Wefirst established a questionnaire consisting of closed questions that we had pre-tested on

several SME managers. The managers of 150 SMEs were interviewed by phone in

November 2001.

The value of the dependent variable was calculated using the initial database. The

choice of an appropriate growth index has given rise to a number of theoretical discus-

sions (Wooden and Hawke; 2000; OECD, 1998; Birch, 1986). As none of the proposed

measures is neutral (Julien, Morin and Glinas, 1998), we decided to use a simple meas-

ure, namely the relative variation (Et - Et-1)/Et-1), as this is the most frequently used

index in studies on growth determinants (Delmar, 1997). In our case, this measure reads:

(E2000 E1994/E1994).

In order to carry out a logistical regression (see infra), these dependent variables were

split into high growth (code 1) and low growth, stagnation or regression (code 0). Wedefined high growth as being growth above or equal to 50% over the period studied. A

total of 34.3% of the firms in our sample can be considered as having undergone high

growth.13

Previous studies differ enormously in terms of the time period studied. In order to

identify irregular short-term tendencies and to allow for a reliable estimation of organiza-

tional performances, the time period studied should be at least five years (Weinzimmer,

Nystrom and Freeman, 1998). On the basis of the constraints of our database, we have

measured growth over a period of seven years, stretching from 1994 to 2000.14


_________________________

10. For the measure of this variable, see next section.

11. From which we withdrew firms that belonged to the examined sample.

12. The major advantage of this method in relation to personal surveys or by post is its rapidity. In comparison

with the personal survey, it also presents a lower risk of bias linked to the person of the interviewer (Lambin,1990). Finally, it allows for the immediate codification of the responses, thus reducing risks of error.

13. The cutoff point of 50% has been chosen in order to generate a proportion of high-growth firms (34.3%)

important enough to generate significant results.

14. During this period, the average annual growth rate of the Belgian GDP in constant prices has been of 2.68%

(Banque Nationale de Belgique).



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So as to avoid static measures, when growth is essentially a dynamic phenomenon, we

have excluded firms that were established during the period studied.

Data Processing

In order to test our hypotheses, we have carried out a binomial logistic regression. Thismethod presents certain advantages in comparison to the standard multiple regression that

is subject to more restrictive application conditions (Garson, 2001; Howell, 1998).15

Among these advantages, we could draw particular attention to the fact that, contrary to

standard regression, logistic regression does not presuppose a linear relationship between

the dependent variable and the independent variables, and does not require a normal dis-

tribution of the variables. We had observed that our dependent variable did not present a

normal distribution. The logistic regression also made it possible to integrate dichotomous

or polytomous and metrical predictors into one single model. Each modality of an origi-

nal variable gave rise to a dummy variable coded 1 if the characteristic was realized and

0 in the opposite case. In order to avoid a linear relation between the independent vari-

ables, for each original variable one of the binary variables created was excluded from the

model. In the case of filtering, in other words when part of the sample is not concerned

by a question, we created a dummy variable composed of the firms not concerned.

Results and Discussion

Prior to the regression, we compared the growth averages of firms that had responded to

our survey with those of the firms who had refused to respond by using a bilateral t-test.

The growth averages for the firms that had responded to the survey were not significant-

ly different from those of the firms that had refused to respond. We then compared the

size, independence and regional location of the firms of the two groups using Pearsons

2 test. Whether the firm had responded or not to the survey is independent of its size at

the start of the period, its independence or dependence and also of its regional situation.

The statistically significant results at the 5% threshold (p < 0.05) of the logistic regres-

sion analysis of employment growth against environment-related variables are given in

Table 1. Only two out of 15 variables have a significant effect on employment growth.

In accordance with our tenth hypothesis, the fact that the company is located in a sci-

ence or industrial park increases the chances of employment growth. This result confirms

the conclusions of other European studies (Colombo and Delmastro, 2002; Westhead and

Storey, 1994). Given a copycat effect, development of networks, easier access to a wide

range of resources and/or scientific research, or agglomeration economies, these companies

grow more rapidly. However, this result does have a potential double selection bias linked

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15. This also represents certain advantages in comparison to the discriminant analysis that can also be used when

the dependent variable is dichotomized. Apart from the fact that the discriminant analysis involves a normal

distribution of the variables, it can give rise to impossible probabilities of success situated outside the 01

range (Howell, 1998).

Table 1. Statistically significant predictors of the binomial logistic regression of employment growth onenvironment-related variables

Independent variables Coeff. SE Wald D.F. Sig. Exp. (b)

Hypothesis 10: location in a science or industrial park 0.799 0.451 3.143 1 0.076 2.224

Hypothesis 13: economically dynamic region - 1.022 0.503 4.126 1 0.042 0.360

2 of the model: 21.316 Sign.: 0.379

Degree of concordance between the predicted values and the observed values: 69.9%



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to the auto-selection processes and/or the selection process implemented by the body

responsible for managing the park (Storey, 1998). Indeed, it is possible that only compa-

nies with reasonable growth prospects might opt to set up business in such a park.

Furthermore, it may be that the organization managing the park might only select compa-

nies with a certain growth potential. Be that as it may, this type of initiative is the onlyenvironmental variable that has a positive influence on growth.

We have put forward the hypothesis that being located in a region that is regarded as

more dynamic than another region could have a positive influence on growth. We meas-

ured the impact of regional location by means of objective and subjective criteria. The

actual region in which companies are located (Wallonia, Flanders, Brussels) does not have

any significant influence on their growth prospects, which is in line with the results of

other studies (Julien et al., 1997). The macroeconomic conditions that prevail in a region

and the measures taken by a regions decision-makers in order to attract capital or busi-

nesses do not therefore have a significant impact on growth, in contrast to more local ini-

tiatives such as the creation of science or industrial parks. Moreover, looking at Table 1,

we are forced to recognize that if a manager perceives that his/her company is part of an

economically dynamic region, this has a negative effect on employment growth. It is pos-

sible that these companies might tend to rest on their laurels on the basis of this per-

ceived regional dynamism at the expense of the real growth of their company.

Both of these variables are linked to the generosity of the environment. Other variables

associated with generositysectoral growth rate, level of concentration in the market, the

existence of entry barriers, obtaining public aid, the perception of fiscal and social pres-

sures, the crime rate and the appearance of the area in which the company is located, the

proximity of university institutions, location in an urban area and the extent of develop-

ment of the road infrastructure, means of transport and communication networksdo not

have any significant effect. Finally, neither dynamism nor environmental complexity

appears to be statistically significant predictors.

Over and above this observation, this tends to show that environment, at least if it is

studied independently of other variables, only has an extremely limited influence on

employment growth of SMEs. Other research that simultaneously examines the impact ofinternal and external variables and the coherence between variables indicates that envi-

ronment does have a significant influence when studied in interaction with internal vari-

ables (Janssen, 2002). Therefore, these results lead us to doubt the ability of purely exter-

nal approaches to explain employment growth. Our results also argue in favour of adopt-

ing an integrative model and an integrative approach in order to study growth. As far as

employment growth of SMEs is concerned, this shows the limits of the explanatory poten-

tial of the structuralist theories or environmental school theories, such as population ecol-

ogy of organizations.

Conclusions

The impact of a companys environment on its growth has prompted considerable

empirical research. However, most of this work focused on the analysis of one or a few

predictors. Furthermore, no research has provided an exhaustive list of all variables pre-viously analyzed. We have tried to fill this gap and have tested the potential influence of

15 environmental variables on employment growth.

Our results show that only two factors linked to the generosity of the environment

have a significant effect on employment growththe fact that the company is located in

a science or industrial park (positive) and the way in which the manager perceives the eco-




12/17

nomic dynamism of the region in which the company is located (negative). Other vari-

ables associated with generosity and variables that are concerned with the dynamism and

complexity of the environment do not represent statistically significant predictors of

employment growth. This observation leads us to question the validity of purely external

approaches to examining growth and to argue in favour of a method that includes bothexternal and internal determinants and considers the fit between them.

The results of our research are subject to certain limitations. First of all, this study is

solely concerned with individual companies. However, some organizations are likely to

grow due to creation of franchises. We did not use groups as our analysis unit, so this type

of growth was inevitably ignored. Furthermore, we measured growth on the basis of data

relating to the start and end of the period. However, growth does not necessarily follow a

regular pattern. The development process may in fact be full of ups and downs.

Nevertheless, our study does not take this phenomenon into consideration, because it does

not take into account intermediate data. Moreover, the type of survey conducted and the

questions asked prevented us from obtaining longitudinal data for a number of variables.

Finally, the methodology that we chose to followto test most of the variables simulta-

neously and not to exclude factors that might seem to be of minor importance at first

sightdoes theoretically dilute the potential contribution of the various predictors.

Another research option that might help overcome this problem would be adopting a more

selective approach based on the results of this research.

As far as future research paths are concerned, subsequent studies on the link between

environment and employment growth could explore two different avenues, possibly even

at the same time. Firstly, since our research showed that only one more local environ-

mental variable (i.e. location in an industrial or science park) has a significant positive

impact on growth, while more macroeconomic variablesat least if these are analyzed in

isolationdo not produce significant results, it would seem appropriate to analyze the

impact of more microeconomic variables on growth. Secondly, our results show that a

purely external approach leads to results that are not particularly convincing. Other rela-

tively isolated studies (Weinzimmer, 1993; Eisenhardt and Schoonhoven, 1990) observe

that environment does have an influence on growth when its interaction with certain inter-nal variables is studied. These interactions may, for example, be concerned with the fit

between entrepreneurial variables and variables associated with the dynamism of the envi-

ronment, between the latter and the organizational structure or between the aggressiveness

of the company strategy and the generosity of the environment. We therefore feel that it

is of paramount importance to adopt a method incorporating these interactions and

extending beyond the external model.

Acknowledgements

This study was conducted with the financial support of the ING Bank.

Contact Information

For further information on this article, contact:

Frank Janssen, Holder of the Brederode Chair in Entrepreneurship, Universit catholique deLouvain, Louvain School of Management, CRECIS, 1, Place des Doyens, 1348 Louvain-la-Neuve,

Belgium

Tel.: +32 10 47 84 28/Fax: +32 10 47 83 24

E-mail: [email protected]

322 JANSSEN



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