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The management and exploitation of external resources has increased and become a new source of business success. This has given rise to various new risks and therefore increased the need for collaborative risk management and learning. The objective of this paper is to explore the differences in risk management and learning across supplier relationships classified through network risks. The paper provides a theoretical review of supplier relationships and risk management, as well as a survey-based empirical study conducted in one case company's supply network. A set of network risks and risk-management measures is developed by means of factor analysis, and a supplier classification by means of cluster analysis. According to the results, the exploitation of collaborative risk management and learning is highest among the most strategic supplier relationships. A classification typology based on suppliers’ opinions helps both parties in the relationship and enables the efficient exploitation of mutual risk management with collaborative learning as one of its keystones.

In recent years the management of external resources has become a new source of business success. To create competitive advantage, organizations have to combine their internal core competencies and capabilities with those of suppliers, customers, and other external resources (see e.g., Doz and Hamel, 1998). Collaboration could be seen as a means of managing and reducing risks, but it also introduces some new risk factors. The focus of this study is on describing the connection between risks in supply relationships and organizational learning as a component of risk management. As suggested by Spekman et al. (2002), a learning supply chain could be seen as a response to uncertainty, which drives partners to collaborate and increases the value of information. However, they also state that the same uncertainty that motivates firms to collaborate also offers the partners a chance to behave opportunistically. It follows that risks and benefits in supply relationships can be connected to each other. There are few theoretical frameworks of risks in collaboration and learning as a means of risk management. Moreover, earlier models of risk-based supplier-relationship classification have been restricted to buyers’ views of supply risk and sellers’ views of customer risk. In the following the suppliers’ own view, which has so far been neglected, is taken into consideration in the classification. Thus, this paper begins to address the practical and theoretical need to explore both network-related risks and collaborative risk management and learning simultaneously. The aim is to study collaborative risk management and learning in different supplier relationships, which are classified through network risks and added-value potential. The first objective is to create a portfolio typology that classifies supplier relationships into clusters. Forms of risk management and collaborative learning are then considered and compared across the clusters. The empirical study was based on a survey conducted in the case company's supply network. The company is a large Finnish original equipment manufacturer (OEM) operating in the metal industry and striving for collaborative relationships with its first-tier suppliers. We developed a survey instrument that includes questions on relationship characteristics, collaborative learning, network risks and risk management. The study comprises 42 suppliers. Measures of risks, added value, risk management and collaborative learning were formulated through factor analysis, and supplier relationships were classified through cluster analysis. The theoretical part of the paper presents a review of the essential literature. Relevant frameworks and models of supplier classification and supplier-relationship management are highlighted, typical risks related to supply networks are then introduced, and lastly forms of collaborative learning and risk management are presented. The empirical part begins with an introduction of the methodology, followed by some background information and a description of the research data. The analysis and results are explained and illustrated, and finally, the implications and suggestions for future research are discussed.

Nowadays companies create their competitive advantage through the combination of internal core competencies and external resources. As the exploitation of external capabilities, especially those of suppliers, increases, the benefits of collaboration and learning will also increase. This is only one side of the coin, however. The growing use of supply networks will also bring along various risks. Thus, it is crucial for purchasing and supply chain managers to identify and develop appropriate forms of collaborative learning processes as a way of better managing risks. In other words, the risks of collaboration should be managed through the benefits of collaboration, i.e. mutual relationship-related learning and joint forms of risk management. Risk management in supply networks is a subject of increasing interest both in academic circles and in industry. However, there are still only a few studies concerning issues related to supply networks and relationships (see e.g., Harland et al., 2003). Another distinct gap in the existing research is the lack of evidence from a wider perspective on risk management, since much of it has been conducted from the buying company's perspective. There is also a certain demand to expand the research field to encompass more quantitative analysis. In this paper we presented a risk-based classification of supplier relationships, and considered the differences in collaborative learning and risk management across supplier clusters. In the literature review we described frameworks of supplier classification, typical risks in supply networks, and relevant perspectives on collaborative learning and risk-management means. The empirical study was conducted as a survey in one case company's supply network. First, learning and risk-management factors based on the results of the survey and literature were formed through factor analysis. Secondly, a similar analysis was conducted in order to define the typical risks and dependencies involved in supplier relationships, and then the suppliers were classified on the basis of these risks and dependencies through cluster analysis. Finally, differences in collaborative learning and risk management were explored across the clusters. Our framework of supplier classification consists of three relationship clusters: non-strategic relationships, in which the mutual dependency and risks are relatively low; strategic relationships, in which the mutual dependency and risks are high; and asymmetric relationships, in which the suppliers’ dependency and risks are high and the buyer's dependency and risks are low. We found that the exploitation of collaborative learning and risk management was significantly stronger in strategic relationships, which was manifest in practice as the use of strategic learning, joint measurement and innovativeness, the protection of relationship-related knowledge, and the amount of communication. Operational learning was significant in all the relationship clusters, indicating the importance of learning in non-strategic and asymmetric relationships, too. A surprising finding was that companies in the asymmetric relationship cluster were not prioritizing their customers, which might have been expected. Our study indicates that the risks and risk-management activities that suppliers perceive in their relationships are predominantly mutual with the customer. It is essential to understand that risks and management activities differ in supplier relationships: risk-based analysis may promote novel thinking in terms of managing them more effectively. Acknowledgement of the fact that it is not all about reducing risks, but also includes managing it, seems to be very important, especially in high-risk strategic relationships. This paper offers contributions in the fields of supplier management and risk management. The risks related to supplier relationships are analyzed from both the buyer's and the supplier's viewpoint, and thus the constructed typology is beneficial to both parties and enables the exploitation of more efficient mutual risk management with collaborative learning as one of its keystones. Alternative and novel methods are also put forward as a basis of supplier classification. The empirical data was collected from suppliers, hence the classification presented is based on their own opinions. On the other hand, this also constitutes a limitation in our study. It could be concluded that the level of risk and dependency in supplier relationship has an effect on the exploitation of risk-management means. Further, strategic collaborative learning could be seen as one form of risk management in strategic supplier relationships. This paper has introduced a relatively simple framework for organizations to classify their supplier relationships and to notice the forms of risk management and learning in different ones. However, there are some limitations, and new questions arise for future research. The study was conducted in one supply network, which clearly limits the generalization of the findings to other research settings. It would therefore be interesting to broaden the view by including several networks of similar or various industries. The optimal use of alternative forms of risk management in different supplier relationships would also offer an interesting avenue for further research.