Exploratory modelling of trust within intra-organizational supply chains

Abstract

The ongoing war between Russia and Ukraine has shown the importance of a well-organized military logistic system. The Dutch Ministry of Defence has concluded that their military logistic system is not used most efficiently. The need to build greater confidence in the ability of a defence organization as a whole to meet and sustain logistic support for future tasks has been acknowledged in the past. One such driver to build greater confidence is that of ‘trust’

Previous research on trust building between supply chain partners has been done manifold. However, the Dutch Ministry of Defence is a unique organization where the roles of distributor and client are within the same organization. Thus we are dealing with an intra-organizational supply chain, rather than a common inter-organizational one. Additionally, as a military organization the main priority of the supply chain is the responsiveness of the supply chain, rather than the efficiency. The uniqueness of the organization is the reason that additional research is needed on the role of trust within the supply chains with these special characteristics.

Multiple variables and their underlying relations, which create complexity and uncertainty, need to be addressed to implement policies that stimulate tryst within the organization. An System Dynamics (SD) Modelling approach will be used to access the dynamic complexity and uncertainty. The Exploratory Modelling Analysis (EMA) workbench enables the use and development of SD models, characterized by dynamic complexity, and deep uncertainty.
The results of the several analysis have given plentiful insights to consider regarding the future of trust dynamics between military supply chain partners. The initial values in a system such as this one have a huge impact on the progress of the model runs. Since the system consists of two major reinforcing feedback loops, Thus the system either strengthens or weakens itself, depending on the initial state of the model. Thus it is important to get the system to such a positive state, since it is likely to remain in a positive state.

As for the policy levers present in this system, the correction capacity lever seems the policy lever to have the most impact on the model outcomes. The correction capacity is the speed of which the incorrect orders get corrected. The results of the analyses conclude that regarding the state of trust in the model, it is crucial to keep this factor as efficient as possible. Since too low performance regarding correcting orders results in such delays that the trust level in the system completely disappears and does not come back within the time frame of the model run.

To summarize, I applied SD modelling and scenario discovery to explore the trust dynamics between a distributor and their client in a military intra-organizational supply chain context. Hereby I proved the importance of the initial state of the system, which due to its structure of reinforcing feedback loops is a big factor for its outcome. Additionally, it shows that the policy lever regarding performance by the distributor has the most impact on the trust level in the system. This insight tells us that performance is the biggest levers to adjust by policymakers to improve trust dynamics within their organization. I recommend policymakers to formulate strategies that give this insight to employees functioning as the distributor as well as the client. The interdependencies between one another should be emphasized. This should give the employees more incentive to improve their performance and thereby build trust between their collaboration partners.