## 4 Literature Review Outcomes
### Interpretation of the Outcomes
Therefore, such reliable information can facilitate the precise analysis of BDA to assist the practitioners about potential points of real selling. Additionally, it can improve other issues related to the pricing of luxury goods to better control such issues and identify the cause of that by BC throughout the SC. These two examples, imply the improvement of doing these activities in terms of reducing over-processing as a Lean waste. Moreover, BDA and IoT can influence Lean efforts in reducing transportation and motion waste in warehouses by real-time analyzing the best product allocation policy. Again, in the warehousing process, the application of BC for specific cases, such as medicine and food, could reduce the time of auditing and inspection by providing data about the originality of materials or expiration dates. Therefore, by doing so BC can reduce waste such as over-processing and waiting. In addition, this can lead to fewer defects by providing instant and reliable data about the real state of the warehouse inventory such as expired products, amount of on-hand inventory, etc. In this regard, it should be combined with IoT for collecting the data, CC for sharing collected information, and BDA to analyze and propose the best decisions by considering different criteria in real-time. In this way, warehouses can have better inventory control and fewer defects. Additionally, for improving remanufacturing and closed-loop SC applying BC and IoT could be beneficial to collect reliable and instant data about the item's remaining life-cycle, expiration date, original producer to return, etc. This can reduce the efforts of over-processing of data and information to achieve a circular economy. Furthermore, the development of BC applications in SC by providing tamper-proof data about suppliers' reliability can also lead to reducing over-processing in the procurement process by facilitating periodic supplier evaluation and providing a more reliable supplier selection process [74]. In this regard, all the suppliers from different echelons should be connected with BC systems that in turn could be integrated with the BDA system to analyze data and CC environment to share data from different supplies location. It can also result in having fewer defects as one of the Lean wastes, due to the fact that a more reliable and trustful procedure for supplier selection leads to improved quality of provided raw materials from the upstream suppliers and fewer defects in the production process. 2. Supply chain-associated issues. As illustrated in Figure 6, the distribution of research papers on SC-associated issues is not homogenous. Thus, researchers should pay special attention to investigating the role of each single technology in improving the SC organization and operations. It seems that due to the novelty of Lean DSC, researchers are mainly focused on information sharing as one of the main aims of digital technologies. However, information sharing is not the focal point for all digital technologies. For instance, in the present literature, AM is just addressed in sustainability issues since by reducing transportation as a waste the amount of carbon emission is also reduced [75]. In this regard, the impact of AM on Lean DSC still should be discovered in the other related issues. For example, AM by reducing lead times can mitigate the risks that are related to disruptions in supply, transportation, and inventory. Therefore, AM can have a significant effect on improving the wastes of waiting, transportation, and inventory. Additionally, AM in combination with CC and BC can help to provide new business models by making novel experiences for the customer service. In fact, AM can promote the capability of product customization in a shorter time with cost-effective procedures. To this end, CC and BC can assist AM to access and share the customized product information in a real-time and reliable manner. Therefore, it leads to reducing the wastes related to waiting, transportation, and over-processing.