Continuously increased order and variability of the inventory in the uppermost level of the supply chain node create the Bullwhip effect. In the context of closed-loop supply chains, this dynamic phenomenon is still little understood despite modern nations' increasing interest in exploring the potential for a circular economy. The problem-specific literature has produced results that are a little bit contradictory. I derive formulas in four archetypes for computing inventory order and variance amplification with different information transparency structures to better understand the Bullwhip Effect in the closed-loop structure. It’s interesting to note that the visibility of the supply chain's degree significantly influences how lead time and return rate affect the performance of that system. From this vantage point, I may review differences from earlier studies. Later on, I switched the perspective of the study from operational to economic. Here, the ideal return rate was established, and the four closed-loop supply chain (CLSC) archetypes where it might be expressed were provided. I demonstrate that the lead times, demand unpredictability, and the cost structure of all nodes affect the ideal rate of return. In this study, I also address pertinent management implications and the properties of various closed-loop systems from the perspective of Bangladesh.