Method to approach

One possible reason for the problems summarised by Lambert and Pohlen (2001, p. 5) could be the fact that a too narrow focus lies on dyadic relationships. As justified by Section 2.4 and in line with our argument (Section 2.2, Section 2.3), there is a need for further research into performance measurement beyond dyadic relationships (Nudurupati, Bititci, Kumar & Chan, 2011), (Bititci et al., 2012) (Melnyk, Bititci, Platts, Tobias & Andersen, 2014). A broader supply chain network perspective or strategy is missing.

It is conceivable that companies may not be able to make the supply chain network visible, either because of a lack of technical knowledge or because of missing available information. Further, it is also possible that companies just do not recognise the importance of holistic performance measurement together with strategy adjustment of their own company (Morgan, 2007, p. 263).

Considering that “practitioners are currently struggling to manage in volatile environments” (Melnyk et al., 2014, p. 183), our approach is to draw relevant lessons for performance measurement by analysing the network what involves the development of a new methodological approach by transferring social network analysis to the business context. The opportunity to quantify network position as one major subject of social network analysis justifies the application of this method. Besides, as a method originating from social sciences, social network analysis is a promising approach to overcome the gap between local optimisation and structural complexities in a network (Basole, Rouse, McGinnis, Bodner & Kessler, 2011).

Commonly, social network analysis focuses on structures such as human groups, markets, world organisation or society in general. In our present context of companies doing business with each other, we interpret the supply chain network as a network of ties. This network is complex and has properties which are not obvious at first hand. The degree of distribution of the connections between the nodes is neither regular nor entirely coincidental. The assumption of a scale-free network (no clear boundaries) is based on a distribution of links per node that follows a power law. Information flows bi-directionally between companies. The broader network perspective is illustrated in Figure 12.

2. Measuring Supply Chain Performance

Figure 12: Scale Free Network Perspective (Wuchty, 2001, p. 1698)

Recognising the existence of a network structure, one possible approach to gain in-depth knowledge for the network design/structure could be behavioural research, either by mass surveys or case studies as means of primary data collection. We suppose that both alternatives have their limitations:

 Surveys require a sufficient amount of feedback. Since it takes time to fill out a questionnaire, people might become reluctant if there are too many requests.

 Case studies are a very interesting alternative. Nevertheless it is difficult to generalise the gained results, because of the limited quantity of feedback.

By contrast, our approach, practiced in this thesis, is the application of social network analysis. Such analysis focuses on the relationships/connections among actors or groups. Transferred to the supply chain network, social network analysis is the descriptive and statistical method to illustrate how the nodes are positioned, connected and embedded within the supply chain network (Bellamy & Basole, 2013, p. 239). Besides, social network analysis allows relationships among actors to be mapped to a graph. The ties between different actors are combined and a network becomes visible. The main goal is the detection of structural patterns such as centrality or cohesion. Social network analysis does not concentrate on an object that is independent of other objects. Instead:

2. Measuring Supply Chain Performance  Social network analysis takes the individual object as an embedded part of a larger

structure.

 Potentially, new findings based on the study of the interrelationships would not be accessible without social network analysis.

 The method assumes that hidden, informal knowledge exists within the structure. The transfer of social network analysis to a business context is either possible within the single organisation or between different organisations. We focus on the second option.

Social network analysis makes different kinds of flows within the network visible and analyses the overall structure. The overall structure may consist of a set of activities, workers, technological and physical infrastructures and policies together with the procurement of raw materials, the conversion to finished and unfinished goods and logistics (Hassan, Mohsen M. D., 2006).

To date, social network analysis has been used in different ways to reveal findings from supply chain networks. Due to the fact, Bellamy and Basole (2013) are the first to provide an “organizing framework to facilitate an understanding of the plethora of supply chain management issues examined using network analysis” (Bellamy & Basole, 2013, p. 236), we refer to Bellamy and Basole’s extensive analysis of publications concentrating on network analysis in the supply chain context. Their review underlines the relevance and increasing interest in this field of research.

According to Bellamy and Basole (2013, pp. 236–237), 126 relevant articles were published between 1995 and 2011. The first article on the level of a network of independent companies (interorganisational) or a network of business units of one lager company (intrafirm) was published in 1995. Out of all 126 articles, only 19 were published between 1995 and 2003. Over 50 % of all articles were published between 2008 and 2011. Figure 13 illustrates the increasing interest in network analysis in the supply chain context.

2. Measuring Supply Chain Performance

Figure 13: Percentage Distributions of the Number of Publications by Year (Bellamy & Basole, 2013, p. 237)

Bellamy and Basole (2013, p. 236) write that one surge in scholarly debate focuses on studies modelling a supply chain system as a complex network of interactions between system entities. The first paper that recognises the network of supply chains as a complex adaptive system is provided by Choi, Dooley and Rungtusanatham (2001).

The application of network analysis in order to engineer a system is practiced in very few cases. According to Bellamy and Basole (2013, p. 236), the main focus is set on product development. No paper deals with network analysis for the purpose of creating and analysing a network of supply chains. Bellamy and Basole (2013) point out a window of opportunity “to review and illustrate the value in adopting the network lens to better understand, design, and manage supply chains as complex engineered systems” (Bellamy & Basole, 2013, p. 236). This research gap is taken up by our thesis. Thus, the following section provides further insights on the relevant themes of social network analysis and what this means for our primary data collection.