Machine learning (ML) is a crucial component of artificial intelligence that has recently attracted attention for its application in logistics. ML algorithms are used on large datasets. They create logic correlations among given data and provide predictions of specific values. This research paper aims to conduct a systematic literature review to showcase the potential applications of machine learning in urban logistics systems, specifically focusing on enhancing satisfaction for postal logistics operators and their customers. The authors used various research publication databases in this context (Web of Science, Scopus, Google Scholar etc). The analysis of different models provides insights into diverse aspects, such as predicting product prices and types of cargo, evaluating user satisfaction, forecasting user departures, assessing optimal geographical locations for implementing postal centres, predicting purchase times before online orders, estimating delivery times in the last phase of the logistics chain and more. The significance of this research is highlighted through the identification of shortcomings in existing literature, offering guidelines for future research in developing new machine learning model for optimal operator selection. This model aims to achieve improvements in both customer and operator satisfaction simultaneously.

The paper explores the key role of the last mile in the evolution of supply chains, with a focus on identifying challenges and solutions applied in the last phase of delivery. Today's challenges for logistics operators have significantly evolved over the past two decades due to current and growing trends. With the rise of e-commerce and urbanization, the last mile becomes a crucial point of competition, where fast, customized, and sustainable delivery emerges as an imperative for all involved stakeholders. The paper is divided into three parts. The first part refers to the identification of challenges faced by logistics operators in the last phase of the supply chain. The second part of the paper provides an overview of existing solutions and strategies that can be used to respond to challenges in the last mile of delivery. The third part offers case studies that provide a comparative cost analysis using different strategies in the last mile of delivery. Through the analysis of various solutions and strategies in the final stage of the supply chain, different aspects of efficiency and costs are illuminated in various scenarios. Understanding these dynamics is crucial for shaping the future of delivery that is efficient, sustainable, and tailored to the needs of the modern consumer.

Support channels represent a unique opportunity to improve customer satisfaction by offering a consistent experience in resolving customer issues. Several surveys show that customers have raised their standards of customer support services. While only a few years ago customers willingly waited a long time to speak with one of the service agents and were patient for their problem to be resolved, today’s customers have very limited patience and want a solution to the problem immediately. Customers don’t want to settle for a mediocre support channel experience. Support channels must provide superior service capacities so that customers see that the company values their choice and time. Efficient management of support centers implies accurate modeling of customer behavior on hold. The subject of our research is the application of data research techniques for predicting customer behavior in support channels. In this paper, we apply machine learning methods to predict customer behavior. Based on historical data in the service system, we use classification algorithms to predict customer patience in service channels.

Interaction channels are special opportunities to improve customer satisfaction by offering a consistent problem-solving experience. Contact center employees are the link between the company and the customer. They are responsible for maintaining an appropriate relationship between the company and the customer. So, they are personally responsible for the customer experience. In this paper, we present an objective evaluation method for evaluating customer-agent interaction, i.e., evaluating the effectiveness of the realization of customer requests from calls. The evaluation method is automatic and does not depend on the relationship between the call center manager and the employees. The motivation for evaluating calls stems from the key performance characteristics of a contact center, of which we particularly emphasize service time, first call resolution, handling time, and others.

Interaction channels are unique opportunities to improve customer satisfaction by offering a consistent problem-solving experience. The role of employees in the contact center is to maintain an appropriate relationship between the company and the customer, thus they are personally responsible for the customer experience. In this paper, an objective evaluation method for evaluating customer-agent interaction, i.e. evaluating calls is proposed. The motivation for evaluating calls stems from the key performance characteristics of a contact center.

The development of information society and broadband Internet is key indicators of social and economic change. They transform the way companies, political systems, and citizens communicate with each other. Today, we talk about various regional and national initiatives to first stabilize and then improve the economies of countries through the development of the Internet and information society. The European Union has recognized information technology as a major factor influencing economic growth and innovation. Among the seven flagship initiatives of the Europe 2020 economic strategy is the Digital Agenda for Europe. This shows the importance that information technologies have in the development of the modern economy. In this paper, we analyze the current state of development of the information society and broadband Internet access in Bosnia and Herzegovina. We highlight the necessity of considering mechanisms for the development of broadband access. We analyzed the current situation and progress in the implementation of the Digital Agenda guidelines in EU countries. The aim of this research is to highlight the advantages of using EU strategic guidelines to improve and develop the current situation in the field of broadband Internet in Bosnia and Herzegovina