# Engineering Supply Chain Transportation Indexes through Big Data Analytics and Deep Learning
## 1 Introduction  
### Supply Chain Transportation Indexes Importance  
Supply chain transportation is an important indicator of economic development from both a macroeconomic and microeconomic perspective, as well as one of the backbones of international trade, able to predict future trends and identify new opportunities for production, distribution, and consumption [1]. According to Statista [2], the market size of the logistics sector is worth ten trillion U.S. dollars globally and is projected to exceed 14.08 trillion U.S. dollars by 2028. These thrilling statistics, coupled with the evolution of smart technologies, come with both opportunities and threats. On the one hand, the explosion of Industry 4.0, which is associated with various innovations, has expandedbusinesses' operations by opening up new markets and increasing the customer base [3]. On the other hand, the occurrence of environmental factors, such as natural disasters and the COVID-19 pandemic, has affected the smooth operations of the industry, resulting in disruptions and increased vulnerabilities [4]. Until recently, the focal point of supply chain management was mainly cost-centered [5]. However, improving the performance of the supply chain requires more than just cutting costs. The elevation of the supply chain to become a source of competitive advantage has forced supply chain firms to adopt an integrated profile in which customer satisfaction is equally important [6]. This holistic approach has forced supply chain transportation firms to establish an environment of consistent supply chain visibility to avoid potential supply chain breakdowns while simultaneously meeting or exceeding customers' expectations by offering exceptional services. The turn of the decade with the onset of the pandemic has highlighted the role of reliability and resilience as key quality factors for the optimization of supply chain transportation [7]. Such optimization is based on specific transportation indexes that assess the health of the supply chain. According to the Bureau of Transportation Statistics, \"The Bureau of Transportation Statistics (BTS) Transportation Services Index (TSI), the Dow Transportation Index, and the Cass Freight Index represent transportation economic indicators that reflect the responses of transportation providers to the economy's demands for moving freight and/or passengers\" [8]. There are several transportation indexes, such as the Freight Transportation Service Index (TSI), the Baltic Dry Index (BDI), the China Containerized Freight Index (CCFI), and the Air Cargo Index (ACI), among others, that serve as important tools to analyze transportation trends and assess the overall supply chain's transportation efficiency. [PERSON] et al. [9], acknowledge the National Logistics Performance Index (LPI) as \"an interactive benchmarking tool to identify possible challenges and opportunities about the performance of trade logistics\". [PERSON] & [PERSON] [10], have developed a social sustainability index for freight transportation systems. [PERSON] et al. [11], propose the LARG index as a risk management tool to respond rapidly and cost-effectively to unpredictable changes and unexpected disturbances within the automotive supply chain. To this end, the performance of the supply chain is affected by specific transportation indexes. To sum up, supply chain transportation indexes are essential tools for performance measurement, economic indicators, industry benchmarking, and risk management that enable businesses to optimize their logistics operations, adapt to changing market conditions, and maintain a competitive advantage. Although several researchers have investigated the sustainability performance of the supply chain through key transportation performance indexes [12], there are still some burning questions in mind. Have global supply chains adjusted to the new digital normal? What is the impact on supply chain transportation indexes due to the advancement of cutting-edge technologies, such as big data?