Elements of context-dependency

When studying the elements of context-dependency, we move from the network level to the company level. When creating the taxonomy of supply networks, Zheng et al.

(1997) and Lamming et al. (2000) distinguish the following contextual variables: i)

market environment, ii) product and process, iii) network structure, and iv) focal firm network strategy. This taxonomy does not go beyond networks, but it provides good elements for the network level analysis. Lehtinen (2001) follows the taxonomy of Johnsen et al. (1998) and Lamming et al. (2000), even though she has classified the supply network variables in more detail, as illustrated in the figure below:

Figure 14. Supply network variables (Lehtinen 2001, 28)

The overview of supply network variables that Lehtinen (2001) describes above provides an extensive framework for analyzing networks. Environment issues can be called external network variables, while strategy, structure, and processes are mainly internal factors, but also part of the environment. When considering the context of the present study, the environmental variables cannot be ignored, as the telecommunication sector is known for market dynamics and uncertainty. This means that many of the variables are common to different business units, for example, the general company strategies and the business environment. Network-related factors have been divided into strategy, structure, and process, from which the process factors are also closely related to product factors. Network evolvement analyzes the

Environment

• Motivation for co-operation vs. vertical integration

• Competitive priorities

• Goal congruence

• Strategy formation Structure

• Length and breadth of network

• Location of key operations

• Development and stage of network

• Power and influence

• Trust

• Dynamics and stability within network Environment

• Motivation for co-operation vs. vertical integration

• Competitive priorities

• Goal congruence

• Strategy formation Structure

• Length and breadth of network

• Location of key operations

• Development and stage of network

• Power and influence

• Trust

• Dynamics and stability within network

specific factors that are important on the relationship-level, as well (trust, as an example), but in the following, the chain and relationship specific factors (dyadic relationships in the model by Harland 1996) will be presented separately.

The chain level factors are comparable to those on the network level. Moreover, since it has been stated that dyadic relationships display the whole network, the supply network variables also match on the relationship level. Additionally, the classification principles of relationships are important to clarify, because some relationships are more strategic or close than others. In general, the relationships vary from short-term, arm’s length relationships to strategic partnerships (Patterson, Forker & Hanna 1999).

Wagner & Boutellier (2002) distinguish two opposite relationships: discrete and relational exchange, where the former one is equal to arm’s length relationships and the latter is closer to partnerships. According to Wasti & Liker (1997), the buyer–

supplier relationship characteristics can be as follows: 1) level of competition in the supplier market, 2) the supplier’s dependence on the customer, 3) performance monitoring activities assessed to the degree that the customer repeats the supplier’s prototype tests for verification, and 4) relationship history. Croom, Romano &

Giannakis (2000) state that important variables influencing relationships between the actors in the network are: i) the sourcing strategy, ii) the attitude and commitment to collaborative improvement programs, iii) the positioning of the focal firm within the total network, iv) the extent of dependencies on the network (proportion of a supplier’s business), followed by the longevity of the relationships, the technological or process links, the existence of legal ties, the degree of power and influence of each party, and the length and complexity of the chain.

Knight (2000) lists key features of the relationships, according to which the relationships between partners can be evaluated. These features are: importance (e.g., strategic), inter-dependence (e.g., mutuality, technology-based, commercially-based), longevity (time in years), character of relationship (adversial, collaborative), contractual relations (partnering, performance related), and complex interface (the number of individuals involved, the degree of integration).

The studies by Johnsen et al. (1999), Lamming et al. (2000) and Lehtinen (2001) propose that product characteristics should be included in the supply network analysis. Indeed, the nature of the product seems to be a significant factor affecting networking activities. Fisher (1997) is one of the often cited authors explaining the relation with the impact of product characteristics on further activities in the supply networks. According to Fisher (1997), a knowledge-intensive product (also innovative product) requires different kinds of decisions than a functional product, as the former must be more market responsive, the demands are more difficult to forecast. Additionally, innovative products have shorter product life cycles, and complex network structures which especially in the upstream of the supply chain shift the emphasis on the management of information. The opposite of an innovative product is the functional product, which is characterized by long product cycles and stable easy-to-forecast demand. (Fisher 1997) Of course, some innovative and unique products are also of lower complexity.

Möller & Wilson (1995) introduce task characteristics as one element in their taxonomy. In the context of this study the development work given to the R&D supplier is considered a task. Task characteristics as reported in Sobrero & Roberts (2002) are asset specificity, means uncertainty, and goals uncertainty. Asset specificity determines the extent to which the activities performed in the relationships have some economic value per se. The level of task uncertainty can be referred to the action or the goal domain. In the first case there are several options by which to achieve the goal. In the latter case the goal itself is unclear.

General models for studying the contexts and activities of networks and relationships have now been presented. These models have been supplemented with other elements inherent in the networks. As a consequence, it is now possible to generate a framework in which the context-dependency of networking activities can be studied.