Espacios. Vol. 33 (12) 2012. Pág. 11


Supply chain management strategies and performance in SMEs within and outside cluster

Suministro estrategias de la cadena de gestión y desempeño de las PYME dentro y fuera del cluster

Simone Didonet 1 y Guillermo Javier Díaz-Villavicencio 2

Recibido: 21-03-2012 - Aprobado: 30-06-2012


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ABSTRACT:
The objective of this paper is to compare the supply chain management (SCM) strategies and the business performance of small and medium-sized enterprises (SMEs) within and outside of cluster. The study aims to examine if SMEs within cluster show better performance than SMEs outside, and if they are capable of taking advantage of the cluster environment to improve their SCM. The analysis is based on a quantitative approach. A binomial logistic regression was carried out with 300 SMEs grouped according to their condition of belong or do not belong to cluster. The results revealed that there are more similarities than differences between the SMEs groups. Notably, the SMEs within cluster do not revealed integration with suppliers and exhibited a weak internal integration. In terms of performance, there were no differences between groups. The paper contributes by providing an understanding of the SCM theme from the perspective of clusters, comparing SMEs within and outside of clusters, an aspect that has not been sufficiently explored in previous studies.
Keywords: supply chain management, small and medium enterprises, cluster, performance.

 

RESUMEN:
Este artículo compara pequeñas y medianas empresas (PyMES) que pertenecen y no pertenecen a clusters en cuanto a sus estrategias de gestión de la cadena de suministro y desempeño. El objetivo es verificar si las PyMES que pertenecen al cluster muestran mejores resultados comparativamente a las PyMES externas al cluster y si aprovechan las ventajas del cluster para mejorar su gestión de la cadena de suministro. Los datos de 300 PyMES son analizados cuantitativamente por medio de una regresión logística binomial, considerando como variable dependiente su pertenencia o no pertenencia al cluster. Los resultados muestran más semejanzas que diferencias entre los dos grupos de PyMES. Contrario a lo esperado, las PyMES pertenecientes al cluster no presentan integración con sus proveedores y exhiben una débil integración interna, considerando las estrategias de gestión de la cadena de suministro. En cuanto al desempeño, no hay diferencias entre los grupos. El artículo contribuye al conocimiento en el área al discutir la gestión de la cadena de suministro en PyMES bajo la perspectiva de clusters, un aspecto aún poco explorado en estudios anteriores.
Palabras Clave: gestión de la cadena de suministro, pequeñas y medianas empresas, cluster.


1.  Introduction

According to the literature, the clusters may be formed exclusively by small and medium sized enterprises (forthwith SMEs) or by a mix of these and large firms, of which this latter group forms the major part (Markusen, 1996).  Independent of the type of cluster, the authors in general agree that there are advantages for firms to belong to these groupings (Doloreux, 2004; Markusen, 1996; Belso-Martínez, 2006; Grando & Belvedere, 2006).  For example, the coordination mechanisms are facilitated by face-to-face interactions and by the fast flow of information in the local context (Chiaverso & Di Maria, 2009), which are the basis for adequate supply chain management (forthwith SCM) (Mentzer et al., 2001).  From this point of view, it can be assumed that the cluster environment could favor supply chain management in the SMEs. 

Nevertheless, various authors emphasize the difficulties of the SMEs in integrating themselves with suppliers and clients (Arend & Wisner, 2005; Stefansson, 2002; Eagan et al, 2003; Bayraktar et al, 2009). In this context, and although the fundamental premise of the studies conducted on SCM up to now is that this practice is beneficial for the firms involved (Stock et al., 2010; Chow et al., 2008), there are some controversies about whether SCM to fit the SMEs and generate benefits for these firms (Arend & Wisner, 2005; Williams, 2006; Stefansson, 2002).  Also, no study has emphasized the relationship between SMEs and large clients in the context of clusters, which complicates the understanding of relationship dynamics between these businesses. 

This work gathers these aspects together and attempts to compare the behavior of SMEs within clusters with SMEs outside clusters, examining the SCM practices and business performance.  The research question to be considered is whether, in consideration of SCM and performance, the SMEs that belong to clusters show better performance than SMEs outside the clusters, and if they are capable of taking advantage of the benefits of the cluster environment. Essentially, the objectives of this study are:

  • To verify the differences between the SMEs that are members of the cluster and those that are not, in terms supply chain integration and the practices of SCM.
  • To determine if the SMEs within clusters show better results than the SMEs outside. 

The study has several major contributions. This is one of the first studies that discuss the relationship dynamics between small and large firms that belong to the same cluster in terms of the benefits generated by cooperation and integration.  Previous studies have discussed the dynamics of the clusters associated with SMEs (Chiaverso & Di Maria, 2009; Doloreux, 2004; Grando & Belvedere, 2006), although they have not considered integration between large and small businesses in the same environment. This aspect assumes importance when considering the strategies of SCM, its adoption and its advantage to SMEs considering their relationship with large firms in the cluster environment. The research also present another perspective little explored in previous investigations: the environment favorable to integration between firms inherent to the cluster, in contrast with the dependence of SMEs on large clients and the impact of this dependence on their actions, strategies and results. This is a characteristic of the clusters studied, where the large firms in the mining sector in the northern region of Chile stand out for being the leaders of the cluster and the SMEs' membership in the cluster is dictated somewhat by their capacity to provide the supplies demanded by them. 

This article is structured in the following way: the next section contains the model and the context of the study. Following that, the theoretical framework and the hypotheses of the research are presented, followed by the methodology used. Next is the presentation and discussion of the results. In the final section, the implications of this study for firms are discussed, as well as the conclusions and limitations of the study.

2. Model and Study Context

The model developed in this study is shown in Figure 1, and proposes that SMEs within clusters, in comparison with SMEs outside, gain advantages from supply chain integration and practices as well as better performance.

         

Figure 1 – Test Model

In this model,  the dimension of supply chain integration includes use of information technologies (henceforth IT) both intra and inter-organizational and in both parts of the chain, i.e., with suppliers and clients (Kauremaa et al., 2009; Bayraktar et al., 2009; Bayraktar et al., 2010; Koh et al., 2007; Quayle, 2003; Bhutta et al., 2007).  With regards to SCM practices, these consist of logistics initiatives of the SMEs which show an emphasis in outsourcing, close location to suppliers and clients, foreign suppliers, and export activities (Kim, 2009; Bhutta et al., 2007; Markusen, 1996; Markusen, 2003; Chiarvesio & Di Maria, 2009; Belso-Martínez, 2006). The performance dimension considers sales volume as a variable of operational performance (Bhutta et al. 2007) and net profit as a variable of financial performance (Kim, 2009).

Upon examination of the relationships established in the model of Figure 1, it is important to consider some aspects associated with the phenomenon under study.  For example, Chow et al., (2008) argue that the practice and structure of SCM can depend on the situation where it is being applied. From this perspective, the market conditions, logistical infrastructure, and the legal and political context of the emerging countries provide a valid context from which to better understand the effective use of the practices of SCM in SMEs (Bayraktar et al., 2010). With these considerations in mind, the SMEs in the northern region of Chile were chosen as an appropriate context for the study.

Chile offers an interesting context for the study due to its macroeconomic profile.  The country occupies first place among the countries of Latin America and the Caribbean in the global competitiveness ranking of the World Economic Forum (2009) due to its potential for sustainable economic growth.  Its commercial openness, macroeconomic stability, and institutional efficiency and transparency are some of the aspects that justify Chile's leadership in the region. Additionally, the country openness index indicates that Chile has an exposure level of 70 percent to international trade (Milesi et al., 2007), which can be translated to greater competitiveness for its domestic industry. 

As for the SMEs, these contribute a total of 13 percent of the country's gross domestic product (GDP) and provide 38 percent of the total employment according to the 2006 data from the National Institute of Statistics (National Statistics Institute, INE, 2008).  In the context of the northern region of the country, these contribute 7.4 percent of the GDP of the district of Antofagasta (where the study was conducted), which is historically known as the 'mining capital of Chile', and where many large multinational copper and mineral extractors operate.  Copper is the main mineral extracted and is the main export product of the country.  In 2006, copper exports represented 56.5 percent of the total of national exports, such that the region of Antofagasta was responsible for just over half of the exports of this mineral (a 54.3 percent of the exports), according to data from the Department of Mining Industry (2006). 

The production matrix in the district of Antofagasta, resembles the cluster of hub-and-spoke type.  The cluster is characterized by the predominance of large mining firms, many of them belonging to foreign multinationals, which possess large economies of scale.  The SMEs are the radials of the cluster and maintain most of their relationships with the large mining firms (Atienza et al., 2006). 

The following section provides a detailed description of the relationship established in Figure 1. Based on an extensive review of the literature, the central argument that supports the model is discussed and the hypotheses associated with the variables studied are developed.

3. Theoretical Framework and Study Hypothesis

3.1 Cluster and Integration of the Supply Chain in SMEs

The literature on clusters emphasizes this model of industrial organization as being greatly affected by its embeddedness in the local or regional context (Markusen, 1996).  In general, the clusters are identified as a model of organization of economic activity capable of overcoming the limits of large enterprises in the paradigm of Fordism (Chiarvesio & Di Maria, 2009).

Regional context forms the basis for understanding these business conglomerations, which provide an answer to the challenge for cities and regions to pledge themselves to income generating activities set against the advances in transportation and information, and the consequent elimination of distances (Markusen, 1996).  In this environment, Markusen (1996) emphasizes new types of groups as is the case of the industrial districts called hub-and-spoke, where the small and medium sized firms (considered the nucleus and origin of industrial districts according to Italian concepts) rotate around one or more dominant firms that are externally oriented.  According to the author, local firms are suppliers to these firms and tend to establish subordinate relationships to them, although in some contexts cooperation between the SMEs and the main firms are established, and these are characterized by their efforts to improve the quality of the suppliers, compliance with time limits, and stock control (Markusen, 1996). 

Also, the mechanisms of coordination are facilitated by face-to-face interaction and fast information flow in the local context (Chiarvesio & Di Maria, 2009).  These aspects emphasize vertical integration between businesses, which would favour the integration and practices of SCM, whose concept is based on firms being part of multiple organizations oriented to the delivery of goods and services to the final consumer (Lambert & Cooper, 2000) and assumes the integration of product, service, finance, and information flows (Mentzer et al., 2001). 

In terms of SCM, various studies have verified that integration and contribution in the chain can deliver important benefits to the businesses involved.  Among these benefits are added value, creation of efficiencies and client satisfaction (Stock et al., 2010; Chow et al., 2008) which are demonstrated by the reduction in inventories, improvements in service delivery, quality improvements, and shorter product development cycles (Corbett et al., 1999). 

Integration of the supply chain assumes activities of interaction with suppliers, undertaking functions both internal to the business and with clients (Kim, 2006).  Among these activities, use of communication and information technologies are key, both intra and inter-organizational, and at both ends of the chain, that is to say, with suppliers and clients (Kauremaa et al., 2009; Bayraktar et al., 2009; Bayraktar et al., 2010; Koh et al., 2007; Quayle, 2003; Bhutta et al., 2007).

In general, the literature indicates difficulties in adoption of IT, and consequently of information systems, on the part of SMEs.  One of the main inhibitors is the scarce resources available to adopt information system solutions that would enable efficient SCMs (Stefansson, 2002; Levy et al., 2002). These systems are expensive and demand sophisticated internal systems, and the SMEs do not have the necessary resources for their implementation (Stefansson, 2002; Bayraktar et al., 2009).  The result can be loss of competitiveness on the part of the SMEs (Kauremaa et al., 2009).  As Stefansson (2002) highlights, large firms utilize electronic data exchange technologies, but experience problems in communications with small businesses when they often do not have sufficient information technology resources, which can exclude them from the logistic operations integrated in the supply chain. 

In most cases, and as in the case of large clients that yield power over the SME suppliers, it is the clients who lead the adoption of inter-organizational information systems (Kauremaa et al., 2009).  Essentially, upon sharing information with its suppliers, large business clients seek efficiency in operating costs and expect to work cooperatively to provide better services, products and technological innovations (Gunasekaran et al., 2004). 

Upon comparing the characteristics and benefits generated from the cluster and SCM, the following hypothesis is proposed: 

H1:  The supply chain integration is favored in SMEs within cluster.

3.2 Clusters and Supply Chain Practices of SMEs

Among the discussions and studies on clusters, several authors attest to the advantages for the SMEs to integrate into these business conglomerations. Chief among these is the facility for outsourcing and exportation (Chiarvesio & Di Maria, 2009; Belso-Martínez, 2006), supported by higher levels of collaboration and easier access to external markets for SME suppliers (Markusen, 1996).  The cluster environment also facilitates interaction between multinational and local businesses through supply management, outsourcing and technical cooperation (Kennel, 2007). 

On studying the spatial configurations in some industrial districts in the United States and Brazil,  Markusen (2003) notes that the relationships between geographically distant businesses can actually turn out to be more important than those of local networks, reflecting the tendency of dispersion in the chain of activities associated with product manufacturing.  This point demonstrates the importance of the development of SCM practices in SMEs within the cluster context.

On the other hand, while comparing SMEs within and outside clusters in the context of the globalization of the supply network, Chiarvesio & Di Maria (2009) point out that the global geographical extension of supply networks stresses SME cluster membership to attain efficiency.  Likewise, under this new competitive setting, SMEs placed in local supply networks are pressured to take advantage of the opportunities presented by globalization and of the advanced SCM practices to increase their competitive advantage (Chiarvesio & Di Maria, 2009).  Included among the practices of SCM are close location to suppliers and clients (Kim, 2009), exportation activities (Bhutta et al., 2007; Markusen, 1996), outsourcing (Chiarvesio & Di Maria, 2009; Belso-Martínez, 2006), and use of non-local suppliers (Markusen, 2003).

Based on these arguments, the following hypothesis is proposed:

H2: The SCM practices are favored in SMEs within cluster.

3.3 Clusters and SME Performance

Before examining the performance of the cluster SMEs, it is important to first consider some particularities that distinguish better results between businesses.  For example, Grando & Belvedere (2006) compared the performance of production and logistics between SMEs, large firms and clusters, and found that firms that belong to these groups showed better results in different performance categories, depending on their condition.  That is to say, better performances are associated with particular characteristics of each typology.  Following the same line, Paniccia (1998, p. 693) states that, "the model of the industrial district is not always associated with superior performance and, even more crucially, other local systems of firms […] show superior results." 

Nevertheless, the logic persists that SMEs belonging to clusters led by large businesses can take advantage of knowledge sharing with their partners to improve their performance by means of mutual cooperation and collaboration (Markusen, 1996), in comparison with SMEs outside clusters.  From this perspective, Porter (1998) argues that, once the members of the cluster are mutually dependent, the good performance of one business can improve the performance of the others.  For the purposes of this study, the performance dimensions considers  sales volume as a variable of operational performance (Bhutta et al., 2007) and net profit as a variable of financial performance (Kim, 2009). 

Based on these aspects, it is proposed that:

H3: The business performance is favored in SMEs within cluster.

4. Methodology

4.1 Sampling and Data Collection

The data utilized in this study were taken from the database of the project 'Demography of the Regional Small and Medium size Enterprises', undertaken by researchers at the Entrepreneurship and SME Center at Universidad Católica del Norte, Chile.  The current database utilizes a sample of 597 SMEs in the district of Antofagasta, northern Chile. The base includes both suppliers and non-suppliers to the mining industry.  The data for the project was collected between September 2009 and August 2010 via a cross-sectional survey. The questionnaires were administered by a team of interviewers via personal interviews with directors or owners of SMEs.  Once they completed the questionnaire component, the project coordinator followed up the work of the interviewers by randomly selecting and then telephoning some of the businesses to confirm the data obtained.  This procedure ensured control over the work carried out and guaranteed the reliability of the information. 

The criterion adopted for the definition of SME was the sales volume of each company, according to the government criterion in Chile. In accordance with this criterion, a SME has an annual sales volume of no less than US$ 234,354.00, and no more than US$ 4,687,096.00 (reference values in Chilean pesos, the national currency, converted to US dollars according to the exchange rate of 6th February, 2012). For the purposes of this study, firms which are suppliers to the mining industry were considered to be within the cluster (identified by the question: ‘are you supplier to the mining companies?’).  Taking into account these criterions, the sample used consisted of 300 companies. Of the 300 SMEs researched, 218 were small enterprises and 82 corresponded to the category of medium sized businesses, according to the criterion for the definition of SMEs that was presented above. Of the sample, 181 SMEs belong to the mining cluster. Table 1 below shows the distribution of companies according to size, and whether they are members of the cluster or not.

Table 1. Distribution of the SME sample according to size and cluster membership

Condition/Size
Small 
Medium
Total
Outside Cluster
102
17
119
Within Cluster
116
65
181
Total
218
82
300

An important aspect to emphasize is the concentration of the SMEs’ sales, an aspect that reveals their dependence upon their clients. Of the total of cluster member businesses investigated, 40 percent of them concentrate between 60 percent and 100 percent of their sales in a single client.  This situation reflects the importance for the SMEs to adjust to the requests of their clients, and to implement practices that improve their operating performance (Bayraktar et al., 2010), as they can be subject to frequent changes in demand and have difficulties in balancing the supply chain (Towers & Burnes, 2008). 

4.2 Research Variables and Measurement

Based on the literature review, an assembly of variables used in this study were defined which represent the dimensions of SCM, and performance applicable to the SMEs. These dimensions are shown in the Table 2.

Table 2 – Research Variables and Measurement

Dimension Item meaured Source
Supply Chain Integration Use of  IT to sell goods and services to clients Bayraktar et al. (2009), Kim (2009), Bhutta et al. (2007), Kauremaa et al. (2009); Koh et al. (2007), Pagell (2004)
Use of IT for post sales service
Use of IT to communicate with clients and suppliers
Client as source of ideas for innovation (close partnership with clients)
Supplier as source of ideas for innovation (close partnership with suppliers)
Use of IT in production
Use of  IT to share information internally
Use of  IT for inventory/stock administration
Use of IT to buy goods and services from suppliers (e-procurement practices)
Supply Chain Practices Closer location to suppliers at a national level Kim (2009), Chiarvesio and Di Maria (2009), Belso-Martínez (2006), Bhutta et al. (2007), Markusen (1996), Markusen (2003).
Foreign suppliers
Outsourcing
Export activities
Close location to clients at a national level
Performance Sales volumen Kim (2009), Bhutta et al. (2007)
Net Profit

Table 2 shows the variables employed in the model and indicates the sources utilized.  The variables of the Supply Chain Integration dimension were originally measures in a continuous scale of seven points, ranging between the extremes of ‘never’ and ‘always’.  Redoli et al. (2008) and Li et al. (2009) use a similar approach to carry out their researches in similar themes. Respondents were asked to indicate the intensity of integration in the supply chain, at one extreme ‘1’ being considered “I never use IT for post sales service” and at other, ‘7’ being considered “I always use IT for post sales service”.  The respondents could mark any point in the scale. The variables of the Supply Chain Practices dimension were originally measures with questions of multiple choice and/or categories.  The same method of measurement was utilized for the measures of performance where the options were “sales volume and net profit in the last three years: has increased, has been maintained, or, has diminished”. 

The variables related to Supply Chain Integration, Supply Chain Practices and Performance were the independent variables in the model. The dependent variable was the membership to the cluster or not, i.e. the SMEs which are suppliers to the mining industry were considered to be within the cluster, and the other group was considered to be outside cluster.

4.3 Data Analysis

a) Preliminary Analysis: Prior to statistical analysis of the data, a check was made for outliers and transformation of independent variables to dummy variables. No outliers were found, reflecting the homogeneity of the sample in term of its characteristics and strategies. In relation to the transformation of variables, this is a recommendation in the case of binary logistic regression (the technique used for the analysis) in the case of multiple types of variables (Pérez, 2001). In doing so, the variables of the dimension ‘Supply Chain Integration’ were transformed in the following way: where one of the extremes corresponded to the option 'never', the value attributed to this option was '0' and to all others a value of '1'.  This decision was taken since, for the interests of this investigation, there was no interest in revealing the intensity of the scale, but rather a simple yes or no, 'does not use' (corresponding to the option 1, 'never' in the original scale), and 'uses' (corresponding to all the other options above 1 through to 7).  As for the dependent variable, this was transformed into categorical, with the value '0' corresponding to SMEs outside the cluster and the value '1' corresponding to SMEs within the cluster.  Then, the SMEs outside the cluster were considered as the contrast group in the model.   

b) Data Analysis: A binary logistic regression was carried out to compare SMEs within and outside clusters in terms of supply chain integration, supply chain practices and performance. Nair & Vidal (2011) applied the same technique to examine the relationship between supply network’s topology and its robustness in the presence of random failures and targeted attacks. The dimensions supply chain integration, supply chain practices and performance were analyzed by means of their respective variables (referred to in Table 2). Rajesh et al. (2011) use a similar approach to carry out multiple linear regressions with independent variables representative of functional dimensions, value chain and strategic capabilities of the third-party logistics (3PL) providers.  Prior to run the logistic regression, a correlation analysis of the independent variables was conducted to verify their independence in the model.  The test revealed only two correlations with values between 0.6 and 0.7 and none over 0.7.  This does not represent a problem for subsequent analysis which implies dependent relationships (Lin & Chen, 2005).

5. Results and Discussion

Table 3 below presents a summary of the results from the binary logistic regression used in testing the hypotheses.  In accordance with the results, the model presents a log likelihood of -339,232 (Nagelkerke R-square = 0,259;  Hosmer and Lemeshow Test p-value = 0,614) indicating that the model adjusted to the statistical parameters. The model classified 71,3 percent of the cases.

Table 3. Results of the Comparison between SMEs Within and Outside Clusters

Dimensions Variables in the Equation
Results
B
S.E.
Wald
df
Sig.
Exp(B)
Supply Chain Integration Uso TIC vender bienes y servicios a clientes
-,028
,364
,006
1
,938
,972
Uso TIC servicio post venta
1,074
,345
9,695
1
,002
2,928
Uso TIC comunicarse con clientes y proveedores
-,483
,658
,539
1
,463
,617
Cliente como fuente de ideas para innovar
,195
,471
,172
1
,678
1,216
Proveedor como fuente de ideas para innovar
-,201
,410
,240
1
,624
,818
Uso TI para producción
,985
,327
9,062
1
,003
2,677
Uso TI para intercambiode info internamente
,762
,459
2,748
1
,097
2,142
Uso TI para administración de inventarios
,130
,454
,082
1
,775
1,138
E-procurement practices
,351
,352
,995
1
,319
1,421
Supply Chain Management Practices Closer location to suppliers at a national level
-,416
,279
2,220
1
,136
,659
Proveedores extranjeros 
,318
,599
,282
1
,595
1,375
Outsourcing
-,305
,280
1,187
1
,276
,737
Export activities
,530
,616
,739
1
,390
1,699
Close location to clients at a national level
,553
,290
3,637
1
,056
1,738
Operational and Financial Performance Volumen de ventas
-,480
,367
1,712
1
,191
,619
Net profit
,222
,364
,373
1
,541
1,249

5.1 Clusters and Supply Chain Integration in SMEs

In accordance with the results shown in Table 3, there is a partial support for H1.

Initially, the significance of 0.002 and positive coefficient of 1.074 for ‘the use of IT in post sales service’ indicates that the SMEs within clusters are highly receptive to integration into the supply chain, in comparison with the SMEs outside the clusters, specifically in terms of the attention delivered to the client after the sale. In general, sales are a significant measure of success in SMEs (Karpak, Topcu, 2011). In this sense, and considering the studied context, this result reveals closeness to the client which is possibly affected by the SMEs' dependence on the clients within the cluster. From the perspective of SCM, these results indicate the need for adjustment to the clients' requests as a way of maintaining the relationship with them (Bayraktar et al., 2010).  According to Boeck et al.  (2009) these requirements are associated with the level of relationship that the SMEs suppliers maintain with their clients and the development of this relationship depends on the SMEs adopting these technologies.

Similarly, supply chain integration is favored in the SMEs within the cluster, through ‘the use of IT in the production process’ and ‘the use of IT for internal information sharing’.  In the first case, the significance of  0.003 and the positive coefficient of 0.985 indicate that the more SMEs are integrated into the cluster, the greater their use of IT in the production process, thus favoring integration into the supply chain, and therefore allowing the partial acceptance of H1.  In the second case,  a positive coefficient (coefficient = 0.762) and significant at a level of 90 percent (p-value = 0.097) for the SMEs within the cluster shows that these firms are used to exchanging information throughout their internal functions via IT, in comparison with the SMEs outside the cluster. 

Conversely, and contrary to expectation, ‘the use of IT to sell goods and services  to clients’, ‘the use of IT to communicate with clients and suppliers’, as well as ‘e-procurement practices’ were not shown to be significant in the model, indicating that these practices are not relevant in the comparison between SMEs.  These results reveal important integration failures of SMEs into the supply chain which persist in spite of the supposedly favorable environment of the cluster to this type of activity. 

Also, not all of the internal functions associated with the production processes in SMEs favor the use of IT.  This is the case in ‘the use of IT for stock management’, which was not shown to be significant in the model, which would indicate that this variable is not important for the SMEs, independent of the context in which they are found (within or outside the cluster). 

In addition, the close partnership with clients and suppliers, represented in this study by the variables: ‘client as source of ideas for innovation’ and ‘supplier as source of ideas for innovation’, respectively, did not show significant results in the model, indicating that these are not practices associated with SMEs both within and outside the cluster. From the cluster perspective, these results run counter to the theory, which describes how the cluster environment favors cooperation between firms (Markusen, 2003), thereby facilitating innovation in these environments (Zeng et al., 2010; Kaminski et al., 2008).  The result suggests that the cluster environment would not be beneficial to the strategic cooperation between SMEs and their suppliers, implying a deficiency in integration into the supply chain.

In general terms, the results allow partial acceptance of the H1 assuming that the integration into the supply chain is weak in the SMEs, and that the cluster environment, in spite of being favorable to some actions of integration, fails to stimulate this type of initiative in the SMEs that would be beneficial for all enterprises involved.  The characteristics of the cluster studied, where the large firms are the leaders and the SMEs their suppliers, show the dependency upon clients for those SMEs not favorable to integration and cooperation.  On the other hand, the non significance of key variables in the integration of SCM emphasizes the difficulties of SMEs in adopting this proposal.

5.2 Clusters and SCM Practices in SMEs

The results presented in Table 3 show very tenuous support of H2, with ‘close location to clients at a national level’ being the only significant variable in the model, with a p-value = 0.056 and a positive coefficient of 0.553. This shows that the cluster environment is favorable to SMEs in terms of sales to domestic clients.  According to Markusen (2003), relationships between geographically distant businesses can turn out to be more important than those of local networks, reflecting a tendency for dispersion of activities associated with product manufacture.  This perspective demonstrates the importance of the development of SCM practices for the SMEs in the cluster context.  Also, complementing Kennel (2007), interaction between large mining businesses (the majority of which are multinational) and local businesses seems to favor SME contact with clients that extrapolate the borders of the cluster. 

Contrary to the expected outcome, the results in all of variables are not significant in the model, indicating that these SCM practices are not associated with the SMEs independent of their condition (within or outside cluster).  For example, with regards to ‘close location to suppliers at a national level’, the results indicate that is not a prominent practice for the SMEs.  The same is shown for ‘foreign suppliers’, where the results are not significant.  In regard to the variable ‘outsourcing’, it was not shown to be a practice associated with the context of the SMEs.  The non significant result of the variable indicates that SMEs from both within and outside of the cluster do not utilize this strategy in supply chain management.  In the case of ‘export activities’,  the result indicates that exportation is not a common practice in either category of SMEs. Observation of the data collected from the firms shows that the percentage of exporting firms is very low, where barely 8 percent of the SMEs affirmed exportation of their products and/or services.  In spite of this, export activity is more frequent in the SMEs within the cluster, which shows an indication (albeit tenuous) that cluster membership may favor this activity.  Results showing export activities as favorable to cluster SMEs were found by Chiarvesio & Di Maria (2009), Belso-Martínez (2006) & Markusen (1996).

From these results H2 is partially and tenuously accepted, indicating that SCM practices are not intensively integrated into the strategies of the SMEs, and are little evident in these firms, although their development could be more favorable from within the cluster environment.

In consideration of the prior discussions on the relationship between SCM and SMEs, the results found for H1 and H2 indicate that the SMEs do not use SCM as a replacement or complement to compensate for their weaknesses in strategic areas such as new product development, quality and service to the client (Arend & Wisner, 2005), and see SCM as a use of power by the large clients, in the arm's length perspective (Quayle, 2003).  Considering that the SMEs are viewed as a dispensable part of the chain (Quayle, 2003), where their function is to provide manufacturing services and support to large clients (Huin et al., 2002), there is little evidence that these firms invest in SCM to receive similar benefits to those obtained by the large firms from the use of these practices (Levy et al., 2002). 

5.3 Cluster and SME Performance

In accordance with the results shown in Table 3, H3 is rejected indicating that the cluster does not provide better performance in the SMEs. 

With regard to operational performance (sales volume), the non significant result shows that this variable is not important for comparison of the SMEs within and outside the cluster.  The same occurs in the case of financial performance, the variable ‘net profit’. This variable was not shown to be significant in the model. 

The results obtained reflect the contradictions identified in previous studies.  According to Paniccia (1998), the cluster model may not always be associated with better performance and other systems adopted by local firms could generate better results.  For Grando & Belvedere (2006), large firms and independent SMEs, as well as clusters can both obtain better performances, depending on the measure of performance used and characteristics of each business type. 

In regard to the group of firms studied, and considering the findings of previous studies, it seems that where the little evidence of mutual cooperation can be found, this is not oriented to improving the performance of the SMEs.  Also, knowledge sharing between partners seems to be insufficient to generate better operational and financial results for the SMEs.  In this sense, the relative high return to capital noted by Markusen (1996) would be present in the large firms within cluster as a consequence of the market power often present in hub-and-spoke clusters as is the case studied.  Similarly, this performance would not be shared with the SMEs. 

6. Conclusions and Limitations of the Study

This research discussed the integration and practices of SCM, and the business performance of SMEs within and outside of cluster. The results revealed that there are more similarities than differences between the SMEs groups.  Notably, the SMEs within cluster do not revealed integration with suppliers and exhibited a weak internal integration. In terms of performance, there were no differences between groups. This is a contradictory result considering that clusters environments favor the performance of the firms. The original contribution of this research is in studying the theme of SCM from the perspective of cluster, comparing SMEs within and outside of clusters, an aspect that has not been sufficiently explored in previous studies.  This work thus increases the studies on SCM  in SMEs conducted by other investigators as Kauremaa et al. (2009), Quayle (2006), Bhutta et al. (2007), Bayraktar et al. (2009), Welker et al. (2008), Arend & Wisner (2005), Cambra-Fierro & Polo-Redondo (2008).  This work also complements the investigations on clusters and/or industrial districts carried out by authors as Markusen (1996 ), Paniccia (1998), Grando & Belvedere (2006), Chiarvesio & Di Maria (2009), Doloreux (2004). Specifically, this work contributes in three ways.

First, this study contributes to the previous studies by revealing the failures in terms of integrating operations into the chain and information flow between the agents.  For Kauremaa et al., (2009), Bayraktar et al. (2009) and Hafeez et al. (2010), SMEs present internal and external barriers which impede use of information systems (IS) as a support to SCM, chief among these are scarce resources and lack of skills.  The findings of this study seem to show these barriers.  For example, the results did not show any association of important aspects of integration into the chain towards the suppliers of SMEs and this was transferred into the cluster environment.  In other words, independent from how the cluster can facilitate the integration, the SMEs in general do not develop these strategies.  From the cluster perspective, it should be expected that the information flow between clients and suppliers will promoted interaction between agents (Kaminski et al., 2008; Markusen, 1996; Grando & Belvedere, 2006; Paniccia, 1998).  On one hand, the results found in this investigation do not follow this logic and reveal some failures in these connections.  On the other hand, they may also indicate that communications are much less formal and are not absorbed in a strategic way so as to contribute to better performances. 

Second, this study corroborates and complements previous results in terms of the weakness of SMEs in adopting SCM strategies.  Although it was expected that the cluster environment would favor this type of strategy, the results provide further evidence of the difficulties of the SMEs in this sense. Furthermore, the cluster environment highlights the perspective of SCM in SMEs, in which it is seen as the use of the power by large clients, via the arm's length perspective (Quayle, 2003).  Also, there is little evidence to show that these firms invest in SCM to capture similar benefits to those obtained by large firms from the use of these practices (Levy et al., 2002). 

Finally, this study reveals a specific context to analysis of the phenomenon, whose market conditions, legal and political context contribute to a better understanding on the effective use of SCM practice in SMEs (Bayraktar et al., 2010; Chow et al., 2008). From this point of view, the SMEs in the northern region of Chile assume the favorable characteristics of the country's openness to international trade markets (Milesi et al., 2007) and sophisticated business context (World Economic Forum, 2009).  Nevertheless, the debate remains open as to whether SMEs in regional mining cluster are taking advantage of the benefits of this opening, and of the technologies and know-how generated by the large multinational firms, with whom they interact in the cluster.  The partial acceptation of the hypotheses reveal that the deficiencies in integration into supply chain on the part of SMEs could be hindering technology transfer and generating lower performances to those potentially expected. 

As a limitation of the research, supply chain management perspective could only be compared between SMEs within and outside the cluster.  Variables such as innovation and enterprise orientation in the environment studied were not considered.  In general, studies on clusters show the importance of these groups in promoting innovation in firms and it would be interesting to study the behavior of these variables using clusters of hub-and-spoke type like the one that was studied.  In this way, studying enterprise orientation of SMEs in these environments would contribute to an understanding of the strategic option of these firms to belong to clusters. 

7. Managerial Implications

The results of this study reveal implications for SMEs in terms of their relationships with large clients and integration into regional clusters.  Some implications for regional governments can also be highlighted. 

In the case of SMEs, belonging to the cluster or not is a strategic option of the firms (Chiarvesio & Di Maria, 2009).  Thus, if on the one hand, cluster membership favors some actions of integration into the supply chain, on the other hand, dependence upon the large clients which lead the cluster seems to monopolize the attention of the SMEs.  This can generate difficulties for these firms in integrating with suppliers and in advancing the practices of SCM.  Assuming that integration into the chain represents cost efficiency and important competitive advantages, failure to include suppliers in the cluster would imply worse performances for SMEs, which to a certain extent was found in the results of this study. 

In the public sphere, this study contributes to the development of public policies oriented to strengthening the position of SMEs.  Essentially, the contribution is in the generation of information regarding relationships established between SMEs and large firms in the regional cluster and failure shown in these interactions. 

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1Department of Administration - Faculty of Applied and Social Sciences Universidade Federal do Paraná – Brazil E-mail: simonedidonet@ufpr.br
2 Partners Consulting Chile Ltda. Antofagasta – Chile E-mail: gdiaz@pconsul.cl


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