Tactical Decisions Research Articles

Forecasting extremes of football players’ performance in matches

This study evaluates the use of simple linear or piecewise linear predictive models to predict extreme performance metrics in soccer matches, based on historical training and to match data of soccer players from RKS Raków Częstochowa football club. The data were collected from January to June 2023. The collected training and matched data average is 9000 records per month. A standard workweek at the RKS Academy consisted of 5 training units and at least 1 match. The best individual models found predict selected game performance metrics with a relative error of 2.3%, suggesting an excellent model fit between prediction and the actual value. This is illustrated by input data metric called “Metabolic Time Zone 5 and 6 Per Distance”, and output data by “Decelarations Total Distance in Zone 5 and 6 Per Distance”—calculated for in 3 min sliding window and characterized by the highest value of the generated parameter based on High Metabolic Load Distance (HMLD). The result concerns models run on aggregated performance metrics developed in APEX-PRO system using expert knowledge in soccer training, while raw GPS location-based models performing worse but still acceptably. Although we believe that the accuracy of the models still has limited reliability, their clarity and up-to-date quality make them useful in the daily planning of training activities and the management of workloads that affect player performance in the upcoming match, as well as the tactical decisions of the coach. More accurate predictions are given by individual models compared to aggregated models (player position), but there are exceptions where group models also perform very well. Adding a second metric to the input did not show a significant difference in the analyzed examples (the results are very similar). Our findings indicate that the model based on metrics from the last match also effectively predict extreme motor performances occurring in the game. In the case of the analyzed player, it was at the input “Accelerations Total Time Per Distance in Zone 6” at the output “Distance in Zone 6”. Specific training or match parameters can be key in predicting exceptional soccer performance, but they can also vary depending on the analyzed player. This confirms the need for further analysis of this issue.

Introducing intermediate wheatgrass as a perennial grain crop into farming systems: insights into the decision-making process of pioneer farmers

The perennial grain intermediate wheatgrass (Thinopyrum intermedium, commercial name KernzaTM) has been proposed as a diversification crop for producing forage and grain and providing ecosystem services to farmers. Although a few studies have addressed farmers’ interests in the crop, information is lacking about the links between farmers’ goals and crop management, i.e., how farmers aim at integrating this crop in their systems. Closing this gap, this paper analyzes for the first time the introduction of intermediate wheatgrass (IWG) from a farmer perspective, as a set of decision plans and goals. The overarching orientations of the farm and organization of the production system, referred as strategic decisions, interact with short-term crop management (i.e., tactical decisions) and farmers’ goals for IWG. In total, 17 individual semi-structured interviews and 2 collective crop management prototyping workshops in France were used to analyze farmers’ rationales as a function of their farm systems, agronomic constraints, and know-how. The study demonstrates that farmers’ interests in IWG revolved around multiple ecosystem services and financial returns. Three ideal-types of farms testing IWG emerged from the relationships between existing farming systems and goals for IWG. The strategic and tactical decisions regarding the integration and management of IWG were contingent on the farming systems, the goals for IWG, the farmers’ know-how, and their ability to mitigate risks. Implications for the future development of intermediate wheatgrass as a niche innovation are considered based on farmers’ points of view. This study provides insights into the ideas and concerns of French farmers regarding IWG and proposes a framework for discussing the introduction of a new crop in a farm system.

How to combine soil and plant indicators to manage nitrogen fertilisation in vineyards?

ContextAlthough grapevine nitrogen (N) needs are moderate, N fertilisation in vineyards requires carefully management because berry development, aromatic composition and hence winemaking are largely influenced by N nutrition. Our objective was to develop a method for reasoned N fertilisation between and during the seasons. MethodsSpecific sensitivities of soil and plant indicators to N supply and availability were estimated and indicator robustness was quantified using contrasted environmental conditions, crop management and N fertilisation in an experimental network comprising five vineyards in southern France over four successive years. The effects of four N fertilisation treatments combining contrasted amounts, forms and timing on the indicators were tested using linear models. Multiple factorial multiple analysis was used to study the effect of environmental and management factors on indicator sensitivity to mineral N fertilisation at budburst. ResultsYield, soil mineral nitrogen at budburst, chlorophyll concentration (SPAD) at veraison, leaf nitrogen content and yeast assimilable nitrogen (YAN) at harvest, were all sensitive to N fertilisation after four years. Different effects of the N treatments were observed from year three for SPAD and from year one for YAN. Additionally, SPAD and YAN indicators distinguished contrasted strategies based on different timings of N supply or the form of N fertiliser. Lastly, the response of the SPAD and YAN indicators was only slightly influenced by pedoclimatic conditions or cultural practices, at least for the variables tested here. ConclusionTwo N indicators measured from veraison (SPAD) to harvest (YAN), can provide valuable information for tactical and long-term fertilisation decisions. Notably, early SPAD information may improve technical vineyard management of interactions between fertilisation and other practices (e.g. weed control or tillage) that interfere with plant N nutrition and enable later correction of YAN values. Combining these indicators with non-destructive imaging techniques should improve N and mineral monitoring in general.

Strategical and tactical supply chain optimisation for smart production planning and control 4.0

Industry 4.0 (I4.0) technologies generate new opportunities for developing smart models, algorithms and tools to support supply chain (SC) production planning and control (PPC), or smart PPC (SPPC 4.0). Paired with opportunities, challenges arise in integrating sustainability and resilience in SC network design (SCND) according under I4.0. The main novelty of this paper is to propose two multi-objective models that integrate strategical and tactical PPC decisions into a sustainable-resilient SC under I4.0 towards SPPC 4.0. Sustainability is incorporated in terms of reducing costs and CO2 emissions, and a job creation factor. Resilience is incorporated in terms of contracting support suppliers. To solve the multi-objective models, the augmented epsilon constraint method (AUGMECON) was used. This algorithm minimises a target objective function while it treats the others as constraints. Our experiments indicate that AUGMECON is sensitive to the choice of epsilon values. Furthermore, a synthetic data generation tool called SR1-SR2_SynthDataGenerator was developed. This tool generates input datasets to validate and evaluate our models against benchmarks. A stochastic model (SR2) is also proposed that, with small datasets, takes 8.39 seconds to solve. The proposed models can be useful for industries that seek sustainable and resilient SCs to adapt to changing environments.

Gamification in the Design of Virtual Patients for Swedish Military Medics to Support Trauma Training: Interaction Analysis and Semistructured Interview Study.

This study explores gamification in the design of virtual patients (VPs) to enhance the training of Swedish military medics in trauma care. The challenges related to prehospital trauma care faced on the battlefield require tailored educational tools that support military medics' education and training. The aim of the study is to investigate how to design VPs with game elements for Swedish military medics to support learning in military trauma care. By understanding the reasoning and perceptions of military medics when interacting with VPs, this study aims to provide insights and recommendations for designing VPs with game elements that are specifically tailored to their needs. The study involved 14 Swedish military medics of the Home Guard-National Security Forces participating in a tactical combat care course. Participants interacted with 3 different VP cases designed to simulate military trauma scenarios. Data were collected through think-aloud sessions and semistructured interviews. The data were analyzed using interaction analysis, structured by the unawareness, problem identification, explanation, and alternative strategies or solutions (uPEA) framework, and reflexive thematic analysis to explore participants' reasoning processes and perceptions and identify possible game elements to inform the VP design. Mapping the military medics' reasoning to the uPEA framework revealed that study participants became more creative after making a mistake followed by feedback and after receiving a prompt to make a new decision. The thematic analysis revealed 6 themes: motivation, "keep on trying"; agency in interaction with VPs; realistic tactical experience; confidence, "I know that the knowledge I have works"; social influence on motivation; and personalized learning. Participants suggested that game elements such as scoring; badges; virtual goods; progress bars; performance tables; content unlocking; hints; challenge; control; imposed choice; narrative; avatars; sensation; randomness; difficulty adapting; competition; leaderboards; social pressure; progression; and renovation can promote engagement, motivation, and support confidence in decision-making. Gamification in the design of VPs represents a promising approach to military medical training, offering a platform for medics to practice medical and tactical decision-making in a risk-free environment. The insights gained by the study may encourage designing VPs with game elements, as well as including possibly wrong decisions, their consequences, and relevant feedback, that may support military medics' reflections and decision-making.

A value chain modeling approach for upscaling the production of fine flavor cocoa in Arauca (Colombia)

AbstractThe fine flavor cocoa (FFC) market offers additional income for small farmers. Despite the potential of several Latin American countries to produce FFC, their lack of standardized postharvest processes hinders compliance with high‐quality standards demanded by the FFC market, as these processes have a direct impact on cocoa's organoleptic characteristics. This work supports the design of a collective postharvest transformation model that coordinates the main steps in the cocoa agri‐food chain: transport of the cocoa harvest, classification, fermentation, drying, storage, and commercialization. Our methodology includes a modeling scheme combining optimization and simulation models, considering variability in the processes, and covering operational (transport and resource allocation), tactical (design and sizing of the processing plant), and strategic (sales dynamics) decisions across the cocoa value chain. We illustrate this methodology in a case study in Arauca, Colombia. Our findings emphasize the importance of combining these operational and strategic models since their inputs and outputs are interconnected influencing the decision‐making within the cocoa value chain. Our study also identifies key determinants for the postharvest design, highlighting the postharvest center capacity, FFC prices, and the market selling mode (export or local).

Disruption Dynamics Maturity Model: An empirical tool for Business Disruption Diagnosis and Intervention

Numerous models and frameworks addressing Digital Transformation and Business disruption have emerged in the last two decades. Generally, such models and frameworks can describe Business disruption well and even help with post-facto analysis as they delve mostly into prior popular examples and cases. The Disruption Dynamics Maturity Model (DDMM) proposed here takes a deeper and more action-oriented approach towards providing diagnosis and a path for possible Interventions. Disruption Dynamics Maturity Model can be applied empirically to business situations, to capture the emerging scenarios and analyze possibilities for the future. While a number of authors, researchers from all over the world and even major consulting firms like McKinsey, Deloitte, Accenture etc. have all tried to gauge this phenomenon, the challenge is that the factors triggering business disruption are becoming more granular and widespread, coming in from multiple directions, mostly not even identifiable in time. This makes it difficult to have a universal or at least a widely accepted model for diagnosing Business Disruption. Hence such a model must be dynamic, evolving in time and must also allow the practitioners or managers to track, group, pre-empt and envision various scenarios allowing them to deduce various strategic and tactical decisions. Through an integrative literature review, this working paper explores and captures significant dimensions to conceptualize such a model which can be used as an empirical tool for Business Disruption Diagnosis and Intervention. The outcome of this study is conceptualizing the Disruption Dynamics Maturity Model and demonstrating its dimensions.

Integrated People and Freight Transportation: A Literature Review

Increasing environmental and economic pressures have led to numerous innovations in the logistics sector, including integrated people and freight transport (IPFT). Despite growing attention from practitioners and researchers, IPFT lacks extensive research coverage. This study aims to bridge this gap by presenting a general framework and making several key contributions. It identifies, researches, and explains relevant terminologies, such as cargo hitching, freight on transit (FoT), urban co-modality, crowd-shipping (CS), occasional drivers (OD), crowdsourced delivery among friends, and share-a-ride, illustrating the interaction of IPFT with different systems like the sharing economy and co-modality. Furthermore, it classifies IPFT-related studies at strategic, tactical, and operational decision levels, detailing those that address uncertainty. The study also analyzes the opportunities and challenges associated with IPFT, highlighting social, economic, and environmental benefits and examining challenges from a PESTEL (political, economic, social, technological, environmental, and legal) perspective. Additionally, it discusses practical applications of IPFT and offers recommendations for future research and development, aiming to guide practitioners and researchers in addressing existing challenges and leveraging opportunities. This comprehensive framework aims to significantly advance the understanding and implementation of IPFT in the logistics sector.

ТЕОРЕТИКО-МЕТОДИЧНІ ОСНОВИ УПРАВЛІННЯ АСОРТИМЕНТОМ ПРОДУКЦІЇ

The article substantiates the importance of managing the range of products in the general management system. It is noted that the assortment policy of a business entity depends on its mission, the developed strategy and tactics, and on the other hand, the assortment policy affects the formation of strategy and determines the tactical decisions of business entities. It is justified that the formation and implementation of the assortment policy of business entities requires a clear idea of the strategic goals of economic activity; clear understanding of one's own capabilities, analysis of the external environment, industry and market trends. It is justified that in the product assortment management system it is advisable to follow the algorithm / procedure for evaluating and improving the assortment structure, which clearly structures the work on the performance of tasks, removes the need to spend time and resources on periodic assignment of tasks to specialists of structural units, etc. The algorithm provides certainty regarding: 1) the frequency of evaluation of the range of products by the business entity; 2) methods on the basis of which the existing assortment structure of production and feasibility of production of potentially new types of products that can be introduced into production will be evaluated; 3) responsible persons (specialists of the structural unit/department) for performing assortment evaluation procedures and preparing conclusions/working out draft decisions regarding the assortment. A model of formation/adjustment of the assortment portfolio of business entities is proposed. Making managerial decisions according to the model should be based on the results of assessing the impact of external environmental factors, the existing assortment structure, the feasibility of introducing new types of products, and the results of assessing the potential / opportunities for expanding production, forecasting and planning, etc.

Enhanced reinforcement learning-based two-way transmit-receive directional antennas neighbor discovery in wireless ad hoc networks

The utilization of directional antennas for neighbor discovery in wireless ad hoc networks brings notable benefits, such as extended transmission range, reduced transmission interference, and enhanced antenna gain. However, when nodes use directional antennas for neighbor discovery, the communication range is limited, resulting in a lack of knowledge of potential neighbors. Hence, it is necessary to design a special antenna direction switching strategy for neighbor discovery based on directional antennas. Traditional methods of switching antenna directions are often random or follow predefined sequences, overlooking the historical knowledge of sector exploration for antenna directions. In contrast, existing machine learning approaches aim to leverage observed historical knowledge to adjust antenna directions for faster neighbor discovery. Nonetheless, the latency of neighbor discovery is still high because the node cannot fully utilize the observed historical knowledge (i.e., only using the knowledge observed by the node in transmission mode, ignoring the knowledge observed by the node in reception mode). Meanwhile, the corresponding reward and penalty mechanisms are still not detailed enough (i.e., these reward and penalty mechanisms only consider the sectors of discovered and undiscovered neighboring nodes, ignoring the scenario of sectors that have been rewarded). In this paper, the neighbor discovery process is modeled as a reinforcement learning-based learning automaton. We propose an enhanced reinforcement learning-based two-way transmit-receive directional antennas neighbor discovery algorithm, called ERTTND. The algorithm consists of a two-way transmit-receive reinforcement learning mechanism (TTRL) and an enhanced reward-and-penalty mechanism (ERAP). This algorithm leverages insights from nodes in transmission and reception modes to refine their tactical decisions. Then, through an enriched reward-and-penalty framework, nodes optimize their strategies, thus expediting neighbor discovery based on directional antennas in wireless ad hoc networks. Simulation results demonstrate that compared to existing representative algorithms, the proposed ERTTND algorithm can achieve over 30% savings in terms of average discovery delay and energy consumption.

Influence of problem-solving ability and personality variables on the improvement and creativity of tactical decisions in basketball.

Basketball players are increasingly required not only to read the tactical actions that take place in a game but also to make correct tactical decisions. This includes greater creativity in the type of solutions they must provide when faced with various tactical situations. To acquire these skills, young players need training in which personality and general intelligence variables significantly influence the learning process. A Perceptual Tactical Training (PTT) program was implemented, correlated with the Eysenck Personality Questionnaire and the Raven's Progressive Matrices test, to observe improvements in tactical perception and decision-making among young basketball players. The PTT produced significant improvements in tactical solutions and tactical perception for all players. Players who scored high in general intelligence found it easier to perceive tactical situations but struggled to generate original tactical solutions. Conversely, players with high psychoticism and high general intelligence were more capable of creating innovative tactical solutions but did not excel in perceiving tactical game situations. Therefore, it is crucial to be aware of the individual differences in intelligence and personality traits among young players to enhance their tactical decision-making and creative abilities.

Optimal product pricing and lot sizing decisions for an omni-channel supply chain

In an omni-channel supply chain, companies offer customers multiple channels to interact with their brand. This allows for greater outreach and sales, resulting in increased customer loyalty and trust. Furthermore, there has been little discussion on the simultaneous consideration of strategic and tactical decisions under return policies in omni-channel supply chains. To maximize total profit, this research proposes a two-echelon supply chain, comprising a manufacturer and multiple retailers, including traditional, electronic and omni-channels. The non-deterministic demand function takes into account the sales price, refund price, delivery time and order quantities. A heuristic algorithm based on analysis of Karush–Kuhn–Tucker optimality conditions used to solve a nonlinear programming model. This research presents an analysis of the factors influencing the decision variables and profit of the entire supply chain and offers retailers a unique way to evaluate their performance and make operational decisions regarding price, delivery time and order quantities.

Workforce Configuration in Charity Settings: A Forward-Looking Approach

Problem definition: Volunteers, the primary workforce for many charities, represent a complex labor pool; they are unreliable and exhibit substantial heterogeneity in both performance and affinity to the organization. Additionally, many volunteers engage not only to contribute but also to immerse themselves in a volunteering experience that, if rewarding, can inspire them to become future donors. However, practical approaches to volunteer management commonly neglect these traits and the consequential impact that tactical decision-making can have on nurturing potential future donations. Methodology/results: Building on a previous study, we propose a forward-looking volunteer scheduling model that accounts for the heterogeneity among volunteers, mitigates both understaffing and overstaffing costs, and explicitly correlates individual time contribution with their monetary donations. We provide analytical solutions when the charity can reliably estimate distributions (e.g., uniform distribution) from data and suggest a distribution-free method to offer actionable insights where data are limited or uncertain. Managerial implications: At the strategic level, by viewing volunteers as potential donors, the optimal staffing strategy balances meeting the charity’s labor needs and maximizing volunteers’ satisfaction, as this satisfaction influences their likelihood of becoming future donors. We show that charities could avert substantial losses by adopting an integrative approach, thereby challenging conventional organizational structures that compartmentalize volunteer and donor management. Our model suggests that building robust data infrastructures can significantly advance the charity’s core mission. Paradoxically, efforts to increase labor productivity may inadvertently undermine this objective. At the operational level, we provide an Excel-based decision support tool and a decision-tree framework to navigate optimal policies, determining when and how a charity can rely on episodic (less reliable) volunteers. Our results confirm that reducing uncertainty in volunteer turnout benefits charities. However, we also find that when labor value is low, episodic volunteers are preferred, whereas formal (reliable) volunteers are favored when labor value is high. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2022.0363 .

Evaluation of the incident management system of a bigger city during the winter flood 2023/24 in northern Germany: Organized (ir)responsibility in the pre-disaster phase

Incident management systems operate within complex and uncertain conditions during disasters. Therefore, researching their activities is challenging as there is no clear right or wrong. The winter 2023/2024 flood event in the city of Oldenburg, Germany, provided an opportunity to evaluate crisis management under high uncertainty, although no disaster has eventually occurred. Three stakeholder groups of the Incident Management System were examined through After-Action Reviews: The Emergency Operation Center (EOC), specialist advisors, and the Area Command (AC). Data on performance shaping factors (descriptions and judgements) were collected and analyzed using the Countenance Evaluation Model as a general framework in combination with a Systems-Thinking approach. The study aimed to identify variables within and between groups as well as factors in the environment that either hindered or facilitated work transactions. It emerged that the work organization in bodies of public administration is at odds with the uncertain, fast-paced, and problem-oriented structure of Incident Management System operations, causing stress and adding workload to employees. Additionally, the separation of strategic and tactical decision making led to coordination issues due to divergent time structures and task logics of EOC and AC. Furthermore, although specialist advisors played a crucial role in risk assessments and setting the direction of risk mitigation activities, it became clear that this person related resource is scarce and difficult to embed into the Incident Command System. A final finding is the importance of the larger Emergency Operation Center working environment. The spatial constraints and noise levels caused stress.

Ranking sports science and medicine interventions impacting team performance: a protocol for a systematic review and meta-analysis of observational studies in elite football

This study protocol describes a systematic method to identify, collect and rank sports science and medicine interventions most associated with optimising team performance in elite football in observational studies. While...

Adoption of Multi-Modal Transportation for Configuring Sustainable Agri-Food Supply Chains in Constrained Environments

Agri-food supply chains have the potential to make a significant contribution to achieving sustainable development goals through ongoing improvements in their configurations. A range of strategic, tactical, and operational level decisions pertaining to the design and operation of sustainable supply chains have been studied in the extant literature. However, investigations into the adoption of multi-modal transportation as a strategic decision in the context of agri-food supply chains operating in constrained environments are limited. As such, in this study, the adoption of bi-modal transportation for the domestic vegetable supply chain in a developing country context under certain constraints was examined. A mixed-integer linear programming model was developed to determine the volume and direction of the product flow to achieve the minimum total food-miles and smallest emissions footprint. As a case study, a Sri Lankan mainstream vegetable supply chain was used to investigate the applicability of a combination of truck and railway modes to transport vegetables from farms to retailer locations via economic (consolidation) centers. The adoption of a bi-modal transportation structure demonstrated the potential to reduce food miles by 32%, transportation costs by 36%, contributions to global warming potential by 35%, and empty truck hauls by 38%, compared to a structure with truck-based, uni-modal transportation.

Condition-based switching, loading, and age-based maintenance policies for standby systems

Standby techniques are widely incorporated in structural design to enhance the inherent reliability of systems. To further leverage the system performance during operation, decision-makers can adopt operational policies to manage system degradation. Specifically, at the system level, unit switching that dynamically determines the online unit contributes to avoiding unexpected shutdowns. At the unit level, adjusting load levels to manage the trade-off between condition degradation and revenue accumulation is crucial for maximizing profit. Additionally, adopting age-based maintenance as a tactical decision, which effectively facilitates the integration of maintenance resources, can be implemented to restore a degraded system. For instance, maintenance is typically scheduled at fixed moments for multi-generator power systems located in remote areas. In between maintenance moments, the proactive switching of generators can ensure uninterrupted output, and the adjustment of load levels for online generators helps to maximize output. Motivated by such engineering practices, this paper investigates condition-based switching, loading, and age-based maintenance policies for standby systems to maximize the expected profit rate in the long-run horizon. The problem is formulated as a Markov decision process. The structural properties of the control-limit switching and monotone loading policies are analyzed for easy policy implementation and efficient problem solutions. For comparative purposes, several heuristic policies are proposed and evaluated. Finally, numerical examples are presented to validate theoretical results and illustrate the superiority of the proposed risk control policy.

Re-design methodology for an under-risk multi-business supply network

ABSTRACT Currently, several supply chains of the same business may be managed independently. This is due to different groups of clients or different marketing channels. Parallely, changes in the environment, due to unexpected situations, lead the decision-makers to modify the configuration of supply chains. Therefore, we propose a redesign methodology based on a progression of steps to study holistic synergies. This design analysis is carried out at a static and dynamic level for strategic, tactical and operational decisions. The use of qualitative and quantitative tools allows a set of solutions to be obtained, which take into account inventory levels, processing times, costs and service levels. To compare the preliminary solutions, AHP (Analytic Hierarchical Process) is combined with TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). It is applied to an example of pharmaceutical distribution in South America. The results indicate an improvement of service levels and a reduction of costs from risks.

Formation Cooperative Intelligent Tactical Decision Making Based on Bayesian Network Model

This paper proposes a method based on a Bayesian network model to study the intelligent tactical decision making of formation coordination. For the problem of formation coordinated attack target allocation, a coordinated attack target allocation model based on the dominance matrix is constructed, and a threat degree assessment model is constructed by calculating the minimum interception time. For the problem of real-time updating of the battlefield situation in the formation confrontation simulation, real-time communication between the UAV formation on the battlefield is realized, improving the efficiency of communication and target allocation between formations on the battlefield. For the problem of UAV autonomous air combat decision making, on the basis of the analysis of the advantage function calculation of the air combat decision-making model and a Bayesian network model analysis, the network model's nodes and states are determined, and the air combat decision-making model is constructed based on the Bayesian network. Our formation adopts the Bayesian algorithm strategy to fight against the blue side's UAVs, and the formation defeats the blue UAVs through coordinated attack, which proves the reasonableness of coordinated target allocation. An evaluation function is established, and the comprehensive scores of our formation are compared with those of other algorithms, which proves the accuracy and intelligibility of the decision making of the Bayesian network.

Improving the Functional Reliability of an Urban Public Transport Line

In this study we consider correlated and simultaneous interventions regarding: i—the physical infrastructure (by crossover lines between the two tracks of a tram line), ii—the characteristics of the trams (by bi-directional trams), as well as iii—tactical and operative decisions of the line manager. How these interventions are reflected in the functional reliability of the tram line service is demonstrated for both cases of the current operation and for the case of overloads, respectively, for the case of the temporary degradation of circulation caused by random disruptive events. The theoretical analysis, generalizing findings regarding the effectiveness of solutions to improve functional reliability, is supplemented with quantitative evaluations related to certain situations of disruptions. The proposed solutions aim to increase the attractiveness of urban public transport. Even if the evaluations are focused mainly on the interests of the service quality perceived by the user, the beneficial consequences for the line manager (in terms of technical and commercial efficiency) are also addressed.