Improving the performance of logistics company using CRM and other techniques.

This thesis delves into the implementation and impact of Customer Relationship Management (CRM) systems within the logistics industry, with a detailed case study of Orion Lift. The research encompasses a thorough financial analysis and logistical performance evaluation post-CRM integration. Orion Lift, a local logistics company, faced several operational challenges, including inefficiencies in customer management and high operational costs. By integrating a CRM system, the company aimed to streamline its processes, enhance customer satisfaction, and improve overall business performance.Financial metrics were meticulously calculated before and after the CRM implementation. The results indicate substantial improvements across all metrics, with notable increases in revenue and customer retention rates, and reductions in operational costs and customer acquisition costs. The thesis also discusses the potential financial and operational benefits of CRM systems, supported by comparative analysis with other effective CRM implementations in the logistics sector. Overall, the thesis provides a comprehensive assessment of the benefits of CRM systems in logistics, using Orion Lift as a case study.

Development of Decision Support Tool for Transport Forwarding Company Operating within Netherlands and Italy

This paper investigates the development of a decision support tool for a Latvian transportation company operating in the Dutch and Italian markets. Models and algorithms for optimizing freight routes using Excel and Python are included. Digitalization of logistics processes is recognized as a key to improve efficiency and reduce costs. Two methods for solving the traveling salesman problem were examined and compared: Excel with Solver and Python with the NetworkX library.The methodology involved collecting data from Google My Maps, creating Excel spreadsheets, and developing Python software to automate route optimization. The results showed that both methods improved route planning, reducing time and cost, as well as reducing carbon footprint.The study emphasizes the importance of integrating technologies such as machine learning and big data into logistics to increase flexibility and adaptability. Recommendations were offered to further improve and implement these technologies for sustainable business development and increased competitiveness in international markets.

Improving efficiency and diversification of services inside a logistics company under price dumping.

Estimating Generalised Transport Costs of Road Freight Transportation in the Baltic Sea Region

This problem of estimating road transport costs in the Baltic Sea region is important for optimising cargo delivery expenses in local transportation and manufacturing sectors. The study incorporates a wider range of economic and logistical factors beyond the usual metrics of physical distance and travel time by using Generalised Transport Costs (GTC). Important factors like geodesic and road distances, travel times, fuel consumption, labor costs, tolls, and other overheads are identified. We utilise a unique dataset that analyses trips between centroids within each NUTS-2 region.The study confirms the GTC model by comparing calculated costs with established database values. Regression analysis uncovers key factors affecting transport costs, such as road distance, travel time, and tolls.Network analysis is used to map the routes in the region, focusing on finding paths that are both cost-effective and time-efficient. The analysis shows how small changes in routes can have a big impact on costs and efficiency.In conclusion, this thesis contributes to the knowledge of road freight transport costs in the Baltic Sea region, offering valuable insights for policymakers and logistics companies.

Application of innovative technologies to organize control over the movement of freight transport.

Bachelor work: „Application of innovative technologies to organize control over the movement of freight transport”.Author of the paper: Anzelika Davidova.Scientific supervisor: Lecturer (program director), Mg. oec. Aleksandrs Kotļars.Paper for obtaining the degree: „Transport and Business Logistics”.The research goal: The goal of this thesis is to develop recommendations for optimizing freight transport traffic control by analyzing innovative technologies such as blockchain, IoT, autonomous vehicles, and ICT.Research object: Management and organization of freight transport traffic control systems.Research subject: Application of blockchain technology to enhance and innovate freight transport traffic control systems.Chapter 1: The role and importance of freight transport in business and entrepreneurship, including its importance in supply chain management and economic contribution.Chapter 2: Analysis of freight transport, with an emphasis on its efficiency, the situation in Latvia and environmental aspects.Chapter 3: Application of innovative technologies in the field of freight transportation, including automated vehicles, autonomous drones and blockchain.