Blockchain Technology for Enhancing Traceability and Efficiency in Automobile Supply Chain—A Case Study

A robust traceability system would help organizations in inventory optimization reduce lead time and improve customer service and quality which further enables the organizations to be a leader in their industry sector. This research study analyzes the challenges faced by the automotive industry in its supply chain operations. Further, the traceability issues and waiting time at different nodes of the supply chain are considered to be priority issues that affect the overall supply chain efficiency in the automotive supply chain. After studying the existing blockchain architectures and their implementation methodology, this study proposes a new blockchain-based architecture to improve traceability and reduce waiting time for the automotive supply chain. A hyper ledger fabric-based blockchain architecture is developed to track the ownership transfers in inbound and outbound logistics. The simulation results of the proposed hyper ledger fabric-based blockchain architecture show that there is an improvement in the traceability of items at different nodes of the supply chain that enhances the Inventory Quality Ratio (IQR) and the mean waiting time is reduced at the factory, wholesaler, and retailer, which thereby improves the overall supply chain efficiency. The blockchain embedded supply chain is more capable to eliminate the risks and uncertainties associated with the automotive supply chain. The benefits of adopting blockchain technology in the automotive supply chain are also described. The developed blockchain-based framework is capable to get more visibility into goods movement and inventory status in automotive supply chains

Blockchain technology for enhancing traceability and efficiency in automobile supply chain: a case study

A robust traceability system would help organizations in inventory optimization reduce lead time and improve customer service and quality which further enables the organizations to be a leader in their industry sector. This research study analyzes the challenges faced by the automotive industry in its supply chain operations. Further, the traceability issues and waiting time at different nodes of the supply chain are considered to be priority issues that affect the overall supply chain efficiency in the automotive supply chain. After studying the existing blockchain architectures and their implementation methodology, this study proposes a new blockchain-based architecture to improve traceability and reduce waiting time for the automotive supply chain. A hyper ledger fabric-based blockchain architecture is developed to track the ownership transfers in inbound and outbound logistics. The simulation results of the proposed hyper ledger fabric-based blockchain architecture show that there is an improvement in the traceability of items at different nodes of the supply chain that enhances the Inventory Quality Ratio (IQR) and the mean waiting time is reduced at the factory, wholesaler, and retailer, which thereby improves the overall supply chain efficiency. The blockchain embedded supply chain is more capable to eliminate the risks and uncertainties associated with the automotive supply chain. The benefits of adopting blockchain technology in the automotive supply chain are also described. The developed blockchain-based framework is capable to get more visibility into goods movement and inventory status in automotive supply chains

The influence of online review adoption on the profitability of capacitated supply chains

The paper explores the influence of online review adoption on supply chain profitability under the presence of a capacity constraint. Nowadays, customers increasingly rely on online reviews for decision making, and online retailers regard reviews as a norm. Although online reviews have been extensively examined in marketing disciplines, little research has been conducted to investigate their influence from a supply chain perspective. In addition, previous research has largely focused on how online review information can influence customer purchase behaviours, but ignores the more basic decision: whether and when companies should adopt reviews. This paper examines the online review adoption decision from a capacitated supply chain perspective through mathematical modelling and simulation. The simulation considers the influence of variables including online review adoption decision, capacity constraint level, lost sales penalty level, and product quality estimation on supply chain profitability. Generally, we find that online reviews can bring more profit to the supply chain than without online reviews, although such influence is moderated by the other three variables. The findings reveal the complexity of the contextual variable impacts on online review adoption, and demonstrate that decisions concerning the adoption of online reviews should take all supply-chain-related variables into consideration rather than only aiming for increasing customer orders

Using simulation to explore the influence of online reviews on supply chain dynamics

This paper extends existing research on the dynamic behaviour of supply chains by including the influence of online reviews. We model an online supply chain which contains customers and one e-commerce retailer. By using simulation, we compare the dynamic performance in a supply chain for two scenarios, namely adopting online review systems and without adopting the systems. The supply chain dynamic performance is measured by bullwhip effect and inventory variance amplification. The results demonstrate that online review systems increase both the bullwhip effect and inventory variance amplification, and this impact can be moderated by product quality, unit mismatch cost, lead time, and customer volatility. We further explore how our model could be extended to include market competition, dual sourcing, online review manipulation, and product returns. As the increase in the bullwhip effect and inventory variance amplification can be associated with supply chain inefficiency, managers who are aware of such consequence induced by online review adoption can make better decisions in supply chain management

The influence of online review adoption on supply chain performance: a hybrid simulation study

Abstract The development of E-commerce leads to the popularity of online review adoption. Customers who purchase online can seek information about products in online reviews posted by others. Although online reviews have become a norm, research mainly focuses on their value from marketing perspectives, with fewer studies linking online reviews to supply chain management. As supply chain management is vitally important to E-commerce, this thesis aims to examine the influence of adopting online reviews on supply chain management. This thesis first conducted a systematic literature review and summarised the mechanisms explaining how adopting online reviews can influence supply chain performance. After that, the thesis followed a positivism research paradigm and conducted hybrid simulations (system dynamics and agent-based modelling) to compare if the influence of online reviews varies between different supply chain configurations. Specifically, the thesis first built a forward uncapacitated supply chain model as a base to investigate how online review adoption can influence supply chain performance. After that, this base model was extended to two further supply chain configurations. One studied the influence of adopting online reviews under the effect of supply chain capacity constraint which is an important factor for production and scheduling in supply chains. Also, the model was extended to consider closed-loop supply chains, given the significance of returns in E-commerce operations. In each scenario, the simulation experiments were conducted in RStudio and analysed by ANalysis Of VAriance (ANOVA). This thesis found that the mechanisms by which online reviews can influence supply chain performance are twofold. The adoption of online reviews can enhance the supply chain communication efficiency and effectiveness. Their adoption can also increase the sensing capabilities of the company. The former mechanism is called ‘connecting-tool mechanism’ while the latter is called ‘data-source mechanism’. This thesis then focused on the connecting-tool mechanism and compared its realisation between different supply chain configurations. In the base model, the adoption of online reviews mainly influenced supply chain demand and revenue, directly determining the supply chain performance. However, when capacity constraints and reverse product flows were considered into the model, the influence of online review adoption became complicated. The results indicated that not only supply chain revenue but also the lost sales and the cost of the reverse supply chain can be affected by online review adoption, and such compound influences from online reviews were contingent on the different contextual factors and led to nonlinear and diverse impacts on supply chain performance. The findings in this thesis contributed to the understanding on how online reviews can influence supply chain performance, enabling researchers to gain deeper insights into the causal relationships between online reviews and supply chain operations. In addition, a generic modelling framework called OR-SCM framework was proposed, providing guidance of mathematical models in this field. For practical implication, the thesis results raised the awareness of complexity in the consequences of online review adoption in supply chains for managers and informed them that, to make better decisions and improve supply chain performance, the adoption decisions of online reviews should be made based on different contextual factors related to supply chains