Networkers with leapwise growth

The differences between non-threatened and threatened networkers wi th leapwise growth are presented in Appendix 6. Statistically significant (p<.05) and almost significant (.05<p<.10) differences between the two groups are presented in Table 7.4.

More entrepreneurs of non-threatened SMEs than others were firm owners who were also founders of the firm. More of them than others had prior work experience both as an employee and as a manager (χ²=2.591; df=1; p=.107). Thus,

varied prior experience seems to be associated with the avoidance of threat in this cluster as in other clusters. There were no big differences between the two groups of SMEs by industry sectors. However, in the sectors of building material, metal, and mechanical woodworking industry, most SMEs had faced threat. It was also characteristic of threatened SMEs that their principles and practices of management had changed more than those of others. On the other hand, acquisitions and mergers were more typical of non-threatened SMEs than others. In addition, more of them than others were regarded as “top firms” in the region. In this cluster, acquisitions and mergers might have provided economies of scale for the SMEs and reduced competition in the field, and thus they might have been important in avoiding threat.

In threatened SMEs, the proportion of products with stable volume was higher. Also, it was more typical of them than others to focus on domestic markets only. Thus, threat seemed to relate to the products which were in a later stage of development and operation in domestic markets only. In contrast, non-threatened SMEs had a higher proportion of new products in the market, and products with growing volume, than others. Importing was characteristic of them. Also, a “we are the first in the market” attitude was more common in their R&D orientation. The biggest customers accounted for a higher share of the firm’s turnover in the non-threatened SMEs than in others. Moreover, typically these SMEs were subcontractors, though their sold subcontracting as a share of turnover was lower than in the case of threatened SMEs. On other words, it seemed that these SMEs were more dynamic than others, and obviously they had stronger symbiotic relations with a few big clients.

The only variable which differed statistically significantly between the two groups was a success factor, ‘investment payments by self-financing’. This, together with long-term customer relations, were valued more highly by non-threatened SMEs than by threatened SMEs. Other success factors related to finance and financial management, logistics, and inno vations were also regarded as more important by non-threatened SMEs than by others, and thus, they might indicate factors which are important for avoiding threat. In threatened SMEs, on the other hand, environmental scanning was given higher priority. Also, strong growth in demand, good reputation, continuity of key persons, personnel training, and customer feedback were considered more important by threatened SMEs than by others. These factors might have been important in avoiding threat. Survival factors more typical of them than of others were personnel’s contribution and flexibility, acquisition of new customers and increased efforts in marketing.

Table 7.4 Statistical differences between the groups in the cluster of networkers with leapwise growth

Variables Test p value

Investment payments by self-financing t = -2.186 (df = 31) .036

Environmental scanning t = 1.941 (df = 31) .061

Long-term customer relations t = 1.851 (df = 30) .074

Changes in principles and practices of management U test (z = -1.701) .089

Being one of the “top firms” χ² = 2.706 (df = 1) .100

A canonical discriminant analysis of the two groups and five variables generated one canonical discriminant function that was significant in distinguishing among the groups (p=.011) (Appendix 5). The discriminant function had an eigenvalue of 0.836 with a canonical correlation of 0.68. Wilks’ lambda value for the function was 0.545.

Thus, the discriminant model explained 45.5% of the total variance between the two groups (df=5, p=.011). All the variables except ‘Environmental scanning’ had over 0.3 value of standardized canonical discriminant function coefficients, and thus, had the highest predictive power. A new discriminant model built on the four variables explained 45.3% of the total variance between the groups (df=4, p=.005). According to the degree of predictive accuracy measured by the percentage of cases classified correctly, 86.2% of the cases were correctly classified. Furthermore, 82.8% of the cross-validated (Lachenbruch 1975: 32) grouped cases were correctly classified.

7.5 Summary and conclusions

The analysis revealed some differences between SMEs that had never been threatened and those that had been at some time. A threat to existence seems to be related to many factors and to vary according to the type of firm. Factors differentiating threatened and non-threatened SMEs were often typical of the cluster of SMEs in question. Moreover, the differences identified by statistical analysis seem to be interlinked to some degree with the causes of the threat and the ways firms adjust as revealed by qualitative analysis. The causes of the threat as well as the ways firms adjust to changing conditions and circumstances seem to be to a large extent cluster specific.

Comparing all threatened and non-threatened firms, several factors distinguishing the two groups of SMEs can be found. In SMEs whose existence had never been threatened, entrepreneurs were more satisfied with business success than those in other SMEs. Also, they thought that their firm’s business success had been better than their competitors’. No differences between the groups were found in terms of the entrepreneurs’ background. However, studies focusing on the causes of failure have found that entrepreneurs of failed firms typically are less educated, less knowledgeable about the industry sector, lack marketing skills, have less experience in

management and entrepreneurship, and are younger, compared with those in survived firms (Storey 1994: 109; cf. Lussier & Corman 1995). It should be noted that the findings concerning the entrepreneurs’ background in this study may be explained at least partly by the changes in management which had happened after the threat in the SMEs studied.

A threat to existence or the absence of such a threat was strongly related to firms in two industry sectors, in particular. Almost all the SMEs in the food industry had never faced any threat to their existence, whereas almost all those in the building material industry had encountered such a situation. This is an interesting finding, since several studies have found that there seems to be no association between failure rates of firms and industry sectors (e.g. Phillips & Kirchhoff 1989; Storey 1994: 94;

Gallagher & Stewart 1985).

More threatened SMEs than others had experienced significant periods of decline, their growth had been fluctuating, and they had had more changes in their business base. Previous studies have also found that changes in business base are associated with lower firm performance (Feeser & Willard 1990). Also, threatened SMEs were older than non-threatened SMEs. However, it should be noted that the SMEs studied were successful firms, and no new firms, i.e. firms less than four years old, were involved in the study. Previous research has found that younger and smaller firms have a lower probability of survival than older and bigger firms. This phenomenon is called ‘liability of newness’ and ‘liability of smallness’ (e.g.

Stinchcombe 1965; Aldrich & Auster 1986: 194-195; North et al. 1992). This is often explained by reference to the accumulated learning of older firms (e.g. Jovanovic 1982) and to the fact that governmental support is targeted more at big firms than at small ones. On the other hand, the longer the time period, the higher the probability that the firm will face a situation in which its existence is threatened, as a result of surprising external market disturbances for example.

The role of the domestic market, excluding the local market, was more important for threatened SMEs than for others, and threatened SMEs expressed more positive attitudes towards interfirm cooperation. Starting or expanding exporting, specialization and cooperation, in particular, were used as ways of adapting. The ability to find quick solutions for changing customer needs was valued more highly by threatened SMEs than by non-threatened ones.

In the cluster of stable independent survivors, entrepreneurs in SMEs that had never had any threat to their existence thought that their firms’ competitive power in the market of the main products was stronger than that of other SMEs. In non-threatened SMEs, the proportion of products with a stable volume was higher, and the proportion of turnover due to the biggest customer lower, than in threatened SMEs.

Many studies report that dependency on one or a few customers is linked with lower

probability of surviving (Storey 1994: 107; Reid 1991; Hall & Young 1991). Non-threatened SMEs had also stayed close to their initial business, and they seemed to attach more importance to the success factors typical of the SMEs in this cluster. It seems that threatened SMEs had more positive attitudes towards interfirm cooperation, and they often operated as subcontractors for other firms.

In the cluster of innovators with continuous growth, entrepreneurs of non-threatened SMEs were almost all founders of their firms, and they often came from the local area. In the case of non-threatened SMEs, the local market’s share in the firm’s sales was higher, and they rarely imported. On the other hand, the R&D attitude “we are the first in the market” was considered more important by threatened SMEs, even though all SMEs in this cluster could be characterized as pioneers in the market. Good inter-personal relations with customers and suppliers and long-term customer relations were considered more important in threatened SMEs than in others.

In the cluster of networkers with leapwise growth, the only variable which differed statistically significantly between the two groups was a success factor, investment payments by self-financing. This together with long-term customer relations were valued more highly by non-threatened than by threatened SMEs. In threatened SMEs, on the other hand, environmental scanning seemed to be given higher priority. Threatened SMEs also had more changes in the principles and practices of management.

When applying discriminant analysis, the most accurate results were obtained when threatened and non-threatened SMEs in the same cluster were compared.

However, there seems to be no single variables with particularly high predictive power. The original discriminant models built on five to ten variables that had showed statistically significant or almost significant differences between the two groups of SMEs, and later, the new discriminant models based on four to five variables with over 0.3 value of standardized canonical discriminant function coefficients explained one quarter to one half of the total variance between the groups. In these models, according to the degree of predictive accuracy measured by the percentage of cases classified correctly, 76-86% of the cases were correctly classified. Furthermore, 70-83% of the cross-validated (Lachenbruch 1975: 32) grouped cases were correctly classified. Thus, it is, indeed, useful to study SME survival within homogeneous clusters of firms.

The results give us some clues about how some SMEs succeeded in avoiding situations where their counterparts had come under threat. For instance, non-threatened networkers with leapwise growth valued the importance of investment payments by self-financing more highly than did other SMEs, indicating that it may be one important factor characterizing their strategic behavior in avoiding situations where their existence could come under threat. In the same way, the more moderate R&D orientation of non-threatened innovators with continuous growth may point to the risks

involved in a more radical R&D orientation. Also, the higher proportion of products with stable volume and lower proportion of turnover due to the biggest customer in non-threatened stable independent survivors may reflect a conscious decision in managing business risks associated with products with changing volume and a high proportion of turnover being due to one customer.

The results reveal potential causes of threat and how the SMEs had succeeded in overcoming the problems they have met. Moreover, the results may reflect the fact that entrepreneurs in the threatened SMEs had learned from the difficulties. For instance, it seems that entrepreneurs in threatened SMEs had realized the importance of interfirm cooperation, which can be regarded as a flexible safety net and as an important way of adjusting to changing conditions and circumstances (cf. Niittykangas 1996). Also, entrepreneurs in the SMEs in the group of threatened innovators with continuous growth valued good inter-personal relations and long-term customer relations more highly than did entrepreneurs in other SMEs, suggesting that those factors might have been extremely important for the survival of these SMEs in their struggle through difficult times.

The results of this investigation shed new light on our understanding of SME survival. The knowledge of successful independent SMEs in peripheral locations presented in the previous chapters could be complemented with the results presented in this chapter. For instance, as shown in the previous chapter, the competitive advantage of innovators with continuous growth was related to their innovativeness. However, this analysis brought out the risks involved in their highly innovative strategic behavior. Also, as shown in the previous chapter, networkers with leapwise growth considered important efficiency and the exploitation of existing business opportunities.

However, new customers may also have great importance for their survival in certain situations.

8 CASE STUDIES: COMPARISONS OF FAILED AND SUCCESSFUL