A logistics service company in Batam faces challenges related to warehouse load fulfillment and sorting inaccuracies. This study aims to identify proposed efficiency improvements to the goods distribution system using the cross-docking method. The research method chosen is cross-docking, a technique that eliminates the storage process in the warehouse, thus saving time and cost. The research findings show significant benefits, especially in achieving zero inventory efficiency. Data processing and discussion revealed that efficiencies were apparent by increasing the sorting tables from 1 to 6, with an output of 90,000 kg during aircraft loading and unloading (compared to approximately 77,000 kilograms). This efficiency arises from the larger output of the sorting tables compared to the input, eliminating the need for warehousing and adding ten trucks. As a result, the shipment can be completed in one trip, with no goods stored in the warehouse. The analysis shows that implementing cross-docking in the company increases efficiency in distributing goods to forwarding partners.

Amid the unfolding Fourth Industrial Revolution, the integration of Logistics 4.0 with agribusiness has emerged as a pivotal nexus, harboring potential for transformational change while concurrently presenting multifaceted challenges. Through a meticulous content analysis, this systematic review delves deeply into the existing body of literature, elucidating the profound capacities of Logistics 4.0 in alleviating supply chain disruptions and underscoring its pivotal role in fostering value co-creation within agro-industrial services. The study sheds light on the transformative potential vested within nascent technologies, such as Internet of Things (IoT), Blockchain, and Artificial Intelligence (AI), and their promise in shaping the future landscape of agribusiness. However, the path forward is not without impediments; the research identifies cardinal barriers, most notably the absence of robust governmental policies and a pervasive lack of awareness, which collectively stymie the seamless incorporation of Industry 4.0 technologies within the realm of agribusiness. Significantly, this inquiry also highlights advancements in sustainable supply chain management, drawing attention to pivotal domains including digitalization, evolving labor paradigms, supply chain financing innovations, and heightened commitments to social responsibility. As we stand on the cusp of technological evolution, the study offers a forward-looking perspective, anticipating a subsequent transition towards Industry 5.0, characterized by the advent of hyper-cognitive systems, synergistic robotics, and AI-centric supply chains. In its culmination, the review presents prospective avenues for future research, emphasizing the indispensable need for relentless exploration and pragmatic solutions. This comprehensive synthesis not only sets the stage for future research endeavors but also extends invaluable insights for practitioners, policymakers, and academicians navigating the intricate labyrinthstry of Logistics 4.0 in agribusiness.

This study aimed to examine and assess the impact of the logistics industry’s environment, entry-level graduates’ characteristics and the logistics and supply chain management (LSCM) program design on the transformation of knowledge and skills at Sohar port in the Sultanate of Oman. The study employed a pragmatic research philosophy involving a structured questionnaire. The sample size included 49 mid-managers from the logistics industry who were working at Sohar Port. The study found that entry-level graduates’ characteristics and LSCM program design positively and significantly influenced the transformation of knowledge and skills. However, the organisational environment had a negative and insignificant impact on the transformation. This study revealed several dimensions that may require further research. It is pertinent to broaden the research scope to other towns, ports, and other countries in the Gulf Council Countries (GCC) to broaden the scope and generalisability of the results. According to the study findings, several recommendations are proposed for the logistics and supply chain sector in Oman to enhance the transformation of knowledge and skills by entry-level graduates, as well as for higher education institutions (HEIs). To meet the sector requirements, HEIs may improve the current university-industry collaborations by increasing the inputs of the industry in designing and developing the LSCM program. The organisational environment must reconsider the knowledge and skills transformation by entry-level graduates in their strategic plan of resources management, which must be emphasised by the remuneration system and career paths incentive. While other studies have explored knowledge and skill transformation in the context of employee training, this study aims to fill a specific research gap by focusing on the transformation of knowledge and skills by entry-level graduates, an area which has not been extensively studied before. Furthermore, this study is unique as it examines the impact of the industry’s environment, entry-level graduates’ characteristics and the LSCM program on the transformation of knowledge and skills within the unique context of Oman. This novel approach provides an opportunity to understand the specific challenges and opportunities faced by entry-level graduates in Oman and suggests strategies for addressing them.

Outsourcing logistics operations is a common trend as businesses prioritize core activities. Establishing a sustainable partnership between businesses and logistics service providers requires a systematic approach. This study is needed to develop a more effective and adaptive framework for logistics service provider selection by integrating diverse criteria and decision-making methodologies, ultimately enhancing the precision and sustainability of procurement processes. This study advocate for leveraging industry-based knowledge in procurement, emphasizing the need to define decision-making elements. The research analyzes nearly 300 logistics procurement projects, using a neural network-based methodology to propose a model that aids businesses in identifying optimal criteria for evaluating logistics service providers based on extensive industry knowledge. The goal of this study is to develop and test a practical model that would support businesses in choosing most suitable criteria for selection of logistics service providers based on cumulative market patterns. The results of this study are as follows. It introduces novel elements by gathering and systematizing unique market data using developed data processing methodology. It innovatively classifies decision-making elements, allocating them into distinct groups for use as features in a neural network. The study further contributes by developing and training a predictive model based on a prepared dataset, addressing pre-defined goals, expectations related to green logistics, and specific requirements in the tendering process for selecting logistics service providers. Study is concluded by summarizing suggestions for future research in area of adopting neural networks for selection of logistics service providers.

Ancient Minipe Anicut, Sri Lanka is world-famous for its engineering excellence. Due to its importance, conserving the ancient anicut, another anicut was constructed downstream in the 20th century. Nevertheless, the water diverted from the ancient anicut to the Minipe Left Bank (LB) Canal was kept as it was due to inherited agricultural importance. This research focuses on studying the contributions made by the adjacent catchment along the Minipe LB Canal. There are several level crossings along the Minipe Left Bank Canal from which the runoff of the local catchment flow into the Minipe LB Canal. Hydrologic Modeling System (HEC-HMS) is used to obtain the yield from each catchment into the Canal, which was compared with the annual diversions from Minipe anicut. The total yield from each stream has been compared with the annual diversion of the Minipe LB Canal from 2014 to 2020. The results obtained from this study reveal that there is sufficient water available for water augmentation in the basin, with an estimated annual average cumulative yield from the catchment of 453.6 MCM. This cumulative yield is 1.7 times the annual average diversion from the Mahaweli River, which is 271.9 MCM. With the findings, it is concluded that there is a potential to augment water from the catchment to address pertaining water shortages conveyance in the command area.