triadic relationships dynamics - se solutionpreet.sesolution.com/iclt2010/full papers/logistics and...
Embed Size (px)
TRIADIC RELATIONSHIPS DYNAMICS
Paul ChilderhouseDepartment of Management Systems,
Waikato Management School, University of Waikato, Hamilton 3240, New Zealand,
Email: [email protected]
Hyung Jun AhnDepartment of Management Systems,
Waikato Management School, University of Waikato, Hamilton 3240, New Zealand
Habin LeeBrunel Business School, Brunel University,
Uxbridge, Middlesex, UK
Wen LuoDepartment of Management Systems,
Waikato Management School, University of Waikato, Hamilton 3240, New Zealand,
Gottfried VossenSchool of Business Administration and Economics,
University of Muenster, Germany
The concept of supply chain management has evolved from focussing initially on functional co-ordination within an organisation, then to external dyadic integration with suppliers and customers and more recently towards a holistic network perspective. A triad is the simplest meaningful sub-element of a network, and as such will be used as the unit of analysis for this research into relationship continuity and information connectivity of triadic parties. The type of interdependence between network players dictates the type of coordination required. Most organisations operate in supply chains with sequential or reciprocal interdependence, both of which require advanced forms of information systems enabled coordination. Networks are dynamic, the connections, working relationships and interdependency evolve over time. Thus any information system solution needs to be reasonably robust to alternative network dynamics. In this paper, we match information systems to supply chain triadic scenarios in an attempt to ensure appropriate connectively.
KEYWORDSSupply Chain Management, Working Relationships, Interdependency, Connectivity
This paper investigates inter-firm interactions from a behavioural perspective. In particular, we examine the relationship dynamics of a network of inter-connected firms with shared end consumers. The social network perspective has gained significant momentum in the management literature (Wang, Heng and Chau, 2007). In this paper we use the psychological concept of balanced theory (Simmel, 1950; Heider, 1958) to make sense of the dynamic inter-relationships of an organisation’s supply chain network. Arguably the most important dimensions of change in business networks concerns the development of activity links, resources ties, and actor relationships bonds (Gadde and Hakansson, 2001).
A triad is the smallest meaningful sub-set of a network (Madhavan, Gnyawali and He, 2004) and as such will be used as the unit of analysis throughout this paper. Figure 1 is a simplistic representation of the multi-layered complex business interactions that make up supply chain networks. The actors are represented by nodes and the connections between them as links. A triadic sub-set of the entire network is illustrated as the grey shaded area in Figure 1. Three actors, ‘A’, ‘B’ and ‘C’ are highlighted and their three links, ‘A’ with ‘B’, ‘A’ with ‘C’ and ‘B’ with ‘C’. Each actor also has a potential mediating role in the relationship between the other two as indicated by the dashed arrow from actor ‘A’ to the link between ‘B’ and ‘C’. Thus we contend that a representative sub-set of a network can be investigated via triads. This cannot be said for dyads that overly simplify the social complexities of real world business interactions.
FIGURE 1THE UNDERLYING TRIADIC STRUCTURES THAT COMBINE
TO FORM COMPLEX SUPPLY CHINA NETWORKS
Balanced theory (Simmel, 1950; Heider, 1958) has been developed in psychology to understand the inter-relationships between individuals. The resultant insight identifies four balanced triads and four that are unbalanced. It is argued that over time certain combinations of positive and negative relationships either remain stable or evolve to one of the alternative possible triadic states. The aim of this research is to use this social perspective on the interactions of individuals to investigate business triads. Once we have established the alternative triadic states we will then go on to explore the communication (links) mediums between each actor, by discussing ways to match information system connectively with the reported eight triadic states.
EIGHT TRIADIC SCENARIOS
Figure 2 provides a visual representation of the eight feasible triadic scenarios with binomial relationship links. On the left hand side is the transactional triad, here the three actors (nodes) are loosely connected (represented by their close proximity to one another) via short term transactions. The next form of triads are the partnerships, here one strong collaborative bound (represented by a link) exists between two of the three actors. There are three alternative partnership triads, obviously based around the alternative combination of pairs. Collaborative triads are the third type of triads illustrated in figure 2. In this scenario one actor is collaborating with the two other actors, but these two are themselves adversarial towards each other. Once more three alterative combinations are feasible, this time based on which actor in the triad is the duel collaborator. The final triadic scenario is the cluster when all three actors collaborate with each other. Simmel (1950), Heider (1958) and more recently Hummon & Doreian (2003) argue that the transactional and collaborative scenarios are unbalanced and will not last in the long term, whereas the partnership and cluster triads are more balanced and hence should provide a business with stable inter-organisational relationships. Each of these alternative triadic states will now be explored.
FIGURE 2EIGHT TRIADIC SCENARIOS
According to Heider’s principles (1958), when every actor only has negative links with the other two, the triad will be unbalance and will be not last. In this transactional scenario all three actors perceive tension with others in the triad. If they want the triad to endure they should attempt to transform one of the negative links to positive to stabilize the triadic structure (Heider 1958; Alessio, 1990) and move to a partnership triad. When all of the links are adversarial in a triadic situation, it is not hard to see that the triad would dissolve if none of the actors wants the relationship to endure. This is very common in the real world, with all three actors taking an adversarial posture toward one another and attempting to maximize their own gain, often at the expense of the others.
Enhancement in overall supply chain performance is a well documented outcomes of partnering initiatives (Jitpaiboon, Dangol & Walters, 2009; Zailani & Rajagopal, 2005; Flynn, Huo & Zhao, 2010). As mentioned in Heider and Alessio’s (1990) research findings, when two indivuals have common negative sentiments to a third person, these two will develop and strengthen their positive sentiments to each other (Heidr, 1958; Alessio, 1990) i.e. your enemy is my enemy, so let’s be friends. These partnerships are thus stable, but the third actor may be replaced overtime because they will be on the outside and may become concerned that the other two actors are scheming against them.
As discussed in Heider’s balance theory and Simmel’s model, when both ‘B’ and ‘C’ like ‘A’, the triadic structure will be unstable if ‘B’ and ‘C’ dislike each other (Heider, 1958; Simmel, 1950; Hummon & Doreian, 2003). Thus this kind of triadic structure will be dismantled reasonably quickly because either ‘A’ or ‘B’ will remove themselves from the triad (Heider, 1958; Hummon & Doreian, 2003). As illustrated by the arrows in Figure 2 these triads will either evolve back towards a partnership by the removal of a link or alternatively by adding a link to form a cluster. In essence the actor with both collaborative links holds the power in this triad, the other two realise this and will therefore attempt to readdress this power imbalance.
Just as in dyadic relationships, cluster organizations treat partners equitably based on mutual trust and co-dependency. This facilitates integrative and collaborative processes and provides continuity for collaboration (Leger, Cassivi, Hadaya & Cya, 2006). As discussed in Simmel’s (1950) triadic research, if individual ‘A’ and ‘B’ know ‘C’ treats them in a different way, ‘A’ and ‘B’ will resist getting any closer to each other. Only after ‘C’ treats both ‘A’ and ‘B’ equally, will ‘A’ and ‘B’ be glad to get together (Simmel, 1950). Furthermore, according to Choi & Wu’s (2009) research, in this kind of triadic structure, the customer is responsible for solving conflicts and building a positive culture
Actor in unbalanced triad
Linking positive relationship Unlikely evolution
Actor in balanced triad
Lack of link, negative relationship
that prohibits opportunistic behaviour. This kind of triadic relationship should last for the long term because all of the three partners collaboratively work together and share the benefits in a win-win-win situation.
INFORMATION SYSTEMS SYMMETRY
Based on our modelling of the triadic relationships, figure 3 shows the mapping between different types of information systems and each triad state, along with a continuum about the degree to which each state is collaborative or transactional. Supply chain portals can best support the relationship characteristics of clusters, whereas B2B exchanges or auctions can be used for transactional triads.
We can expect the adoption of the information systems suitable for the balanced states facilitate the proposed evolution from unbalance states to balance ones. For example, adoption of Extranet, EDI, and e-procurement systems can facilitate the transition from transactional to partnership triads. Building a supply chain portal can similarly help companies transit from collaborative to cluster triads. Therefore, our model and propositions can also be useful for helping organisational select and adopt suitable information systems to stabilize their supply chain relationships in the long term.
FIGURE 3TRIADS AND SUPPLY CHAIN INFORMATION SYSTEMS
The conceptual exploration of relationship dynamics between three organisations has provided valuable insight into the potential stability and evolution of supply chain networks. The role of a mediating actor bringing other actors together requires considerable more research. Our next steps are to fully explore this new perspective on social networks through case based comparisons of a multi-national sample. The references are available on request.
Available on request