Basim Aljabhan

Saudi Arabia, as world’s leading oil exporter and the greatest economy in the Middle East, is pursuing Saudi Vision 2030 with the aim of transforming the country into the region’s main lo-gistics hub connecting Asia, Europe, and Africa. To achieve this vision, the Saudi Government has enacted widespread developments in all logistics-related fields. The Logistics Performance Index (LPI) is an important assessment and comparison tool created by the World Bank. This research paper examines the relationship between Saudi LPI components and Saudi foreign trade exports and imports for 2007–2018. Statistical Package of Social Sciences used to measure the correlation coefficients, and hypotheses testing followed in order to determine the statistical significance of the coefficients.Economic globalization and competition have greatly enhanced the role and im-portance of logistics on both the micro and macro levels. To compete in international markets and gain a better global market share, countries and businesses must produce high-quality export products at lower prices, and they must do so with lower logistics costs. Accordingly, these actors want to assess their logistics system performance, as as-sessment is key to enhancing the system’s capabilities and to optimizing and developing its components. Popular assessment tools include the Agility Emerging Markets Logistics Index, the Global Competitiveness Index, and the Logistics Performance Index (LPI).

The fierce competition in international markets and the rapid advancements in information technology result in shorter lead times, lower transportation capacity, and higher demand. The supply chain network is one of the most crucial areas of concentration in the majority of business circumstances. Blockchain technology is a promising option for safe information exchange in the supply chain network. Although preserving security at every level of the blockchain is somewhat important, cryptographic methodologies are frequently used in the existing works. The novel perceptive craving game search (PCGS) optimization algorithm is used to optimally generate the key for data sanitization, which assures the privacy of logistics data. Here, the original logistics data obtained from the manufacturer is sanitized with an optimal key generated by using the PCGS optimization algorithm, avoiding the risk of unauthorized access and data swarm that causes the system to lag. Moreover, the sanitized data obtained from the manufacturer is transmitted to the allowed parties via different sub-chains. The same generated key is used on the receiving customer side for reconstructing the original information from the sanitized data. The performance and results of the proposed blockchain-based privacy preservation model are validated using various parameters.

Social dimensions of sustainability are far less discussed in the spectrum of sustainability. As suppliers are able to influence decisions across a supply network, we argue that the considerations for the social aspects of sustainability should begin from the process of supplier selection. Integrating social sustainability into the supplier selection process can ensure that firms can focus on the wider aspects of sustainability. We use a sustainability framework for social sustainability to identify the social sustainability factors for supplier selection. Based on this and the related literature, we identify and classify the factors into six categories of human rights and equity, health and safety, wages and benefits, education and training, child and bonded labor, and, finally, philanthropy and ethics. Furthermore, we propose a two-layered grey stratified decision-making (GSDM) model for identifying the best suppliers, by considering the attributes of social sustainability, along with the primary performance attributes of supplier selection, subject to a set of diverse objectives. A case evaluation and implementation of the proposed methodology has been conducted in the context of an electronics manufacturing industry in India. Here, we address the specific problem of social sustainability-based supplier selection, and the methodology is novel, as it can address the problems with compensatory aggregation in multicriteria decision-making situations. This research helps in increasing the awareness among firms regarding social sustainability and the related factors, and their prominence for a supplier selection problem, focusing on the sustainability theory extended to firms. Considering the practical implications of the study, managers and practitioners can ascertain the importance of social sustainability and the related factors in any strategic decision-making situation, including supplier selection.

This work explores the leading supply chain processes impacted by big data analytic techniques. Although these concepts are being extensively applied to supply chain management, the number of works that examine and classify the main processes in the current literature is still scarce. This article, therefore, provides a classification of the current literature on the use of big data analytics and provides insight from professionals in the field in relation to this topic. A well-established set of practical guidelines was used to design and carry out a systematic literature mapping. A total of 50 primary studies were analysed and classified, chosen from a sample of 5, 437 studies after careful filtering to answer six research questions. In addition, a survey was prepared and applied by professionals working in the area. In total, 25 professionals answered a questionnaire with eleven questions, ten of which seek to explore the importance of big data analytics for the areas of the supply chain addressed in this work, and one intends to list the three areas where BDA can be more shocking. More than 60% of the studies are directly linked to the area of chain management; most studies performed empirical studies but rarely classified or detailed methodological procedures; almost 50% bring models to optimize some process or forecasts for better decision-making; more than 50% of professionals working in the area believe that the processes where big data analytics can effectively contribute are related to inventory and stockout management. This study serves as a basis for further research and future work, as it reviews the literature, pointing out the main areas that are being addressed and making a relationship with understanding these areas in practice.