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.

Factors affecting customer loyalty in the logistics service
industry

In this study the author conducted a survey among 68 employees of different companies, 31 of them representing logistics companies and 37 employees of companies that are users of these services in order to analyze the obtained data using the PLS-SEM method and to identify the key factors affecting the formation of customer loyalty. Based on the identified factors the author proposes a concept of measures to increase customer loyalty of small road freight transportation companies in Latvia.Chapter 1 provides theoretical information on the process of selecting a logistics service provider and a description of the factors used in this process. The basics of the creation of customer loyalty and measures to increase it were also considered.Chapter 2 includes the analysis of the freight transportation market in Latvia, analysis of logistics companies in Latvia and analysis of the data obtained from the survey.Chapter 3 contains a statistical model showing the most important factors affecting customer loyalty of logistic companies. Based on the statistical model, a concept of measures to increase customer loyalty of small logistics companies is proposed.