Perspectives on Various Issues of Interest

Amphibious vehicle for humanitarian relief

In a sudden-onset emergency, World Food Program uses an amphibious truck that looks like a tank with inflatable wheels. It is called a Sherp — a name that suggests the fortitude of one who scales Mt. Everest loaded with a pack.

After field-testing two Sherps in the Democratic Republic of Congo and three in South Sudan in 2018, WFP included two of the Ukraine-made vehicles in the response to Cyclone Idai in Mozambique. Before the Sherp could proceed, however, crucial navigational information is needed. Sherps can’t climb a vertical wall, so the driver needs to know where the slopes tapered off. It is important to avoid rapids. A drone is used to get a bird’s eye view of the area.

Images from the drone are broadcast onto the phone screen of the pilot driving the vehicle, so he could ‘see’ past the tree tops and the swamp, and is able to navigate the area. 

In 48 hours, 26 metric tons of food were moved into Buzi, one ton at a time, the drone leading the Sherp across the unpredictable river.

Once the operation in Buzi was completed, the amphibious vehicles were moved back to Beira, ready to assist in the next flooded area. With two Sherps warehoused in the Southern Africa region, WFP and the Mozambique National Institute of Disaster Management (INGC) now have more cost-saving options for reaching stranded populations.

Source: The humanitarian monster truck. By Tej Rae

Complex Adaptive Systems Paradigm in Operations and Supply Chain Management Research

In a recently published article we present a conceptual model for a renewed consideration of the complex adaptive systems (CAS) perspective in operations and supply chain management research. In the paper we discuss the following conceptual issues and their relevance in operations and supply chain management research:

1) Constituents of a complex adaptive system

2) Nature of coevolution

3) Embracing Complexity

Building on the theoretical foundation around the above listed issues we describe the following conceptual model:

The paper offers several directions for future research. Operations and supply chain outcomes rely on certain search processes aimed at improving the local performance of the firms in the network. A CAS perspective can unravel the search process and present a deeper understanding of how overall performance improvement can be achieved. It can be particularly useful to study indirect effects within several operations and supply chain problems where there is no obvious relationship between cause and effects. The CAS perspective can help in understanding the process as well as the outcome of pattern formation that are evident in many situations pertaining to operations and supply chain management. As an example, norms in buyer– supplier relationships take shape through a collective pattern that can be examined by considering the CAS perspective. The CAS perspective calls for considering part “ in vivo.”  Investigating how changes in one part affect others and the behavior of the whole can help in assessing the inherent nature of CAS, such as supply networks. In this regard, this CAS perspective can help in further discerning how control and emergence operate in supply networks. 

Structure is typically viewed as a linear contingency variable in extant research. Studies adopting a complex systems perspective have shown that structure can also act as a nonlinear contingency. Similar considerations would help in disentangling the general and local effects within operations and supply chain management. Routines, replication, and inheritance form the cornerstone of several OSCM practices. The CAS perspective can help in better understanding how these aspects contribute toward short-term efficiency and long-term learning outcomes in organizations. Additionally, relaxation of the rationality assumptions can help in discerning the emergent properties of agents in operations and supply chain management contexts.

The paper also provides directions for new methodological approaches such as latent space models and latent class models (e.g., stochastic block models), entropy measures, Reynold's number, attractor geometry, fractal dimensions, and others.

Source: Nair, A. and Reed‐Tsochas, F., 2019. Revisiting the complex adaptive systems paradigm: Leading perspectives for researching operations and supply chain management issues. Journal of Operations Management, 65(2), pp.80-92.