Business Example:
case study 1

Fuzzy Cognitive Maps

FCMs provide a graphical model of the behaviour of a dynamic system through a graph representation. In the graph, concepts are represented as nodes and the associations between the concepts are represented as weighted edges.
The nodes are connected by signed and weighted edges representing the causal relationships that exist among concepts.

1st Added value: The interconnections between concepts are evaluated through linguistic values.

eij=0 indicates no causality relationship between concepts Ci and Cj;

eij>0 indicates positive causality between concepts Ci and Cj

eij<0 indicates negative causality between concepts Ci and Cj

FCM used within the
Research Approach

Case Studies:

•Home Appliance SC;

•Fashion SC;

1st Case Study: Home Appliance SC

Step 1: Problem identification

• How do different factors influence SCR within the “home appliance” sector?
• How do the same factors influence themselves within the “home appliance” sector?

Step 2: Literature research, factors affecting SCR

Research Parameters:
“Supply Chain”  AND (“Resilience” OR “Risk” OR “Risks” OR “Disruption” OR “Disruptions” OR “Sustainable” OR “Supply Chain Uncertainty” OR “Supply Chain Uncertainties”)

Result: 86 research articles

Filters:

•Ensure substantive relevance, defined as adequacy of the articles in addressing;

•Consider only English language articles;

•Remaining abstracts should be read for substantive relevance;

•Remaining full articles should be read for substantive relevance;

Result: 39 research articles

Step 3: Taxonomy

Research Parameters: The factors were then grouped into concepts, to find an optimal trade-off between comprehensiveness and conciseness

Step 4: FCM Design

Question: Does the «Concept i» influence the «Concept j»?

Step 5: FCM Refinement
Step 6: Hidden Pattern Identification


2nd added value:

Local view – Global view

Step 6: Hidden Pattern Identification


Indirect Effect:
(I_k (C_i,C_j )=min{├ e(C_p,C_(p+1) )}&)
The equation can be explained with the metaphor “a chain is only as strong as its weakest link”. If in the chain a weak connection exists, it is not possible to consider the chain as a “resistant chain”, but the total “strength” of the chain is quantified with the “strength” of the weak connection

Total Effect: (TE(C_i,C_j )=max{├ I_k (C_i,C_j )}&)

Bibliography

• Bevilacqua, M., Ciarapica, F. E., Marcucci, G., & Mazzuto, G. (2018, October). Conceptual model for analysing domino effect among concepts affecting supply chain resilience. In Supply chain forum: An international journal (Vol. 19, No. 4, pp. 282-299). Taylor & Francis.

Bevilacqua, M., Ciarapica, F. E., Marcucci, G., & Mazzuto, G. (2018, October). Conceptual model for analysing domino effect among concepts affecting supply chain resilience. In Supply chain forum: An international journal (Vol. 19, No. 4, pp. 282-299). Taylor & Francis.