Positioning a Small Carrier in a Market Dominated by Large Players: Building a Microstrategy

2025 Vol. 2 No. 3 https://www.eujini.org.pl 24 ISSN 3071-9658 https://www.eujini.org.pl Positioning a Small Carrier in a Market Dominated by Large Players: Building a Microstrategy Yevhen Liestiev 1 * 1 Kyiv National Economic University named after Vadym Hetman, Kyiv (Ukraine). CEO, Larus Logistics LLC. *Corresponding Author, e-mail: [email protected] ARTICLE INFO ABSTRACT Research Article Received: 15 July 2025 Revised: 3 September 2025 Accepted: 21 September 2025 Published online: 15 October 2025 Copyright © 2025 by authors This is an open access journal and all published articles are licensed under a Creative Commons Attribution— NonCommercial 4.0 International (CC BY-NC 4.0) DOI: 10.5281/ zenodo.18071222 The aim of the article is to improve methodological approaches to developing a microstrategy for positioning a small carrier in the freight market to ensure a competitive advantage in the conditions of dominance of large logistics operators. The study uses systems analysis for market segmentation, mathematical modeling of the nonlinear dependence of demand on resource capacity, as well as statistical methods for forecasting demand, taking into account cyclical fluctuations. Methods of route optimization, analysis of operational efficiency, modeling of flexible logistics scenarios and assessment of client interactions are applied. Analytical models are based on the principles of maximizing the expected operational effect and taking into account the probabilities of demand deviations. A microstrategy is proposed that focuses on localized market segments (peripheral areas, agricultural zones, industrial parks), where small carriers have an advantage due to speed, flexibility and personalization. A structural and functional transportation management model has been developed, including route optimization, flexible planning, dynamic pricing, a hybrid model of regular and one-time transportation, as well as individualized agreements with customers. The dependence of demand on operating activity with three zones has been established: insensitivity, effective growth, and saturation. Adaptive logistics tools have been proposed, in particular, a portfolio of customers with opposite cycles and capacity reservation, to smooth out seasonal fluctuations. An analytical model of a forecast production program takes into account resource constraints and ensures a balance between demand and capacity. The concept of “dynamic demand” has been developed, which allows a small carrier to actively influence the volume of orders through adaptive mechanisms. A unique positioning model has been proposed that integrates speed, flexibility, and personalization as key competitive advantages of small enterprises in logistics. The study deepens the understanding of the competitive strategies of small carriers, clarifying the role of market segmentation, adaptive logistics and individualization in conditions of limited resources, which contributes to the development of the theory of logistics management. The proposed tools (route optimization, flexible planning, dynamic pricing, customer base diversification, short-term contracts) allow small carriers to increase operational efficiency, stabilize cash flows, minimize the impact of seasonality and ensure the sustainability of the business model. The implementation of microstrategy contributes to the formation of customer loyalty and the creation of long-term partnerships, which increases competitiveness at the local level. KEYWORDS microstrategy, positioning, small carrier, freight transportation, adaptive logistics, dynamic pricing. Yevhen Liestiev , 2(3) https://www.eujini.org.pl 25 Introduction ynamic processes changes in logistics systems and high competition in the freight road transportation market, dominated by large operators with a powerful fleet and extensive infrastructure, small carriers are forced to look for effective ways to adapt to constantly changing market conditions. The dynamic market situation, which is formed under the influence of fluctuations in demand, variability of supply and price volatility, requires business entities not only to respond promptly to external factors, but also to implement strategically verified solutions in the field of managing the profitability and efficiency of logistics processes. In view of the above, the construction of a microstrategy for positioning a small motor transport enterprise operating in conditions of limited resources, a small client base and high dependence on the random nature of orders, in particular for intercity freight transportation, becomes particularly relevant. For such carriers, the key factor in maintaining profitability is not only the performance of a one-time flight in the forward direction, but also ensuring the profitability of the return flight, which is often complicated by the unpredictability of the availability of cargo at the required loading point (Naumov, 2023). The lack of a counter-order forces a small carrier to make a difficult management decision: to wait for a profitable offer or return empty-handed with financial losses. It is in this context that the justification of an individual microstrategy for positioning a small carrier becomes a necessary condition for ensuring its competitiveness in the market, which is characterized by a high level of concentration of large players and an uneven distribution of logistics flows. Scientific understanding of the behavior models of small carriers in the segment of one-time orders of intercity transportation allows not only to optimize their actions in conditions of uncertainty, but also to form clear approaches to market segmentation, definition of the target audience, as well as building an effective strategy for responding to changes in the market situation (Vasylenko et al., 2024). The relevance of this area of research is due to the need to create an effective strategic management toolkit capable of ensuring the sustainable development of small transport enterprises in an environment of logistical challenges and commercial risks. Literature Review n the scientific field, attention is paid to the general aspects of the interaction of the transport operator with other participants in the transport system, in particular with cargo owners, with the main emphasis on fulfilling the customer's requirements for the type of transport, transportation conditions and the choice of carrier. In the studies of Ahmed (2024), Görçün et al. (2024), the consideration of the information and financial component prevails, while the technological and operational features of the organization of transportation often remain outside the scope of analysis. Despite this, there are almost no scientific works that would consider in detail the specifics of the strategic behavior of a small carrier, limited in resources and deprived of access to centralized management systems. The issue of building an adaptive operating model for a micro-enterprise, which is forced to work in conditions of high competition and unstable demand, is also insufficiently covered. Selected publications by Bishara et al. (2025), Pfoser (2022), Xu, J. (2025) state the need for periodic adaptation of the carrier's strategy to changes in the external environment, emphasizing the influence of regional, economic and legal factors on the efficiency of the transportation process. It is argued that any strategy is variable and subject to adjustment in accordance with changes in demand or resource availability. However, in the scientific field, a unified approach to the implementation of such adaptations has not yet been developed, namely in the format of a microstrategy, as a targeted tool focused on local resources and a limited geography of service. In a number of published works Lai (2024), Matuszak Flejszman et al. (2024), Siryk et al. (2024), presents technological aspects of the transportation process, in particular its division into sequential stages and identification of inefficient operations, which allows optimizing costs and reducing delays. It is noted that the structuring of the transportation process is an important factor in reducing losses and increasing efficiency. However, these conclusions mainly concern systemic transport structures and do not take into account the peculiarities of the work of a small operator, in particular the need to simultaneously perform the roles of a planner, dispatcher, executor and controller. Separately in the works of Bugayko et al. (2024), Lafkihi et al. (2025). Xing et al. (2023) analyze aspects related to cargo safety during transportation, including damage, accidents and theft. It is noted that most of the D I Yevhen Liestiev , 2(3) https://www.eujini.org.pl 26 risks are associated with personnel errors, insufficient instruction or neglect of the specifics of the cargo. The authors propose standardized security measures, but their implementation often requires specialized systems, financial investments and personnel training, which are difficult to implement at the level of a small carrier. In this context, solutions are not sufficiently developed on how small carriers can reduce risks with a minimum budget: for example, by implementing simple control procedures, mobile communication with drivers, reducing route length or cooperating with a limited number of reliable customers. In general, a review of scientific literature indicates that although general approaches to transportation management are actively researched, the issues of positioning a small carrier in the conditions of dominance of large companies, adapting the operating model to demand dynamics, and optimizing solutions within limited resources remain scientifically insufficiently studied and require in-depth research, which is implemented within the framework of this article. Problem Statement he purpose of the article is to substantiate the principles of forming a microstrategy for competitive positioning of a small transport enterprise in the field of freight transportation under the conditions of dominance of large logistics companies in the market. Research objectives: – To analyze the current trends in the evolution of the freight transportation market and establish the characteristic features of the activities of small carriers in conditions of high concentration of logistics services. – Create an analytical diagram of the relationship between the degree of use of the resource potential of a small carrier and changes in demand, taking into account the zones of optimal efficiency, overload and underutilization. – To offer practical means of implementing microstrategy, including route planning, flexible schedule management, combined portfolio service and personalized customer service. – to develop mathematical patterns of the transport operator's predictive operational program, taking into account the stochastic nature of demand and resource constraints, to achieve the highest expected operational result. Methods and Materials he methodological basis was a system analysis, which allowed segmenting the market by geographical (peripheral areas, agricultural zones, industrial parks) and client (small and medium-sized producers) characteristics. To model the dependence of demand on resource capacity, nonlinear mathematical modeling was used using functions describing zones of insensitivity, effective growth and saturation. Demand forecasting was based on statistical methods, in particular regression analysis taking into account seasonal fluctuations, using data processing software. Route optimization was carried out using dynamic planning algorithms that take into account order density, geographical proximity, traffic and time constraints of customers. To assess operational efficiency, the criterion of maximizing the expected operational effect was used, which takes into account the probabilities of demand deviations from the predicted values. The hybrid service model (regular and one-time transportation) was developed based on the analysis of client portfolios with opposite logistics cycles. Results and Discussion icrostrategy acts as a management tool that allows a small carrier to form a stable competitive position, even in an environment where systemic advantages remain on the side of large players. The first and critically important stage of building a microstrategy is segmentation of the freight transportation market in order to identify those subsystems within which a small carrier can realize its relative competitive advantage. Unlike large operators that seek to cover large regions and ensure integration into nationwide or international logistics chains, a small enterprise should focus its efforts on servicing localized segments and territorial clusters characterized by a constant need for small or medium-volume transportation, repeatability of orders T T M Yevhen Liestiev , 2(3) https://www.eujini.org.pl 27 and low accessibility for large structures due to the geographical or economic inefficiency of the latter. Optimal geographical areas for effective service may be peripheral areas of large logistics hubs, agricultural areas with seasonal surges in transportation needs, and medium-scale industrial parks that generate stable but not too large cargo flows (Department of Infrastructure, Transport, Regional Development, Communications and the Arts, 2024). Target customer segments, in turn, may be small and medium-sized manufacturers who require a flexible service schedule, individual transportation conditions, and quick response to changing circumstances, i.e., precisely those characteristics in which small carriers are able to outperform bulky competitors. The microstrategy of a small carrier involves building a logistics service model that would be as different as possible from the universal mass approach typical of large companies, and at the same time focus on those advantages that are difficult to scale or standardize. In conditions of a limited fleet and narrow specialization, three key parameters take priority: the speed of decision-making and order fulfillment, the flexibility of logistics scenarios, and the depth of service personalization (Grytsenko & Fedorchuk, (2024). In this case, speed refers to both the minimization of administrative procedures between receiving a request and the departure of transport, and the possibility of prompt delivery without long-term planning. Small carriers, devoid of a multi-level management hierarchy, are able to respond to requests almost instantly, which is extremely appreciated when providing urgent or non-standard transportation. Flexibility is manifested in the ability to adapt the route, loading or unloading time, and type of vehicle to the characteristics of the cargo or client requirements (Makedon et al., 2024). Personalization, in turn, involves not only maintaining direct contact with the client, but also maintaining a history of orders, taking into account individual wishes regarding transportation conditions, and building long-term relationships with an emphasis on mutual trust. This component creates loyalty and forms the reputation of the carrier, which does not just provide services, but also solves the client's problems. A feature of the activities of a small carrier is the high dependence between the degree of resource utilization and the volume of demand that it is able to satisfy. In practice, this means that even a slight excess of the fleet's throughput capacity (especially during peak periods) can lead to a decrease in the quality of service, delays and loss of customers. While insufficient utilization causes unproductive costs and reduced profitability. Demand response modeling involves building a function in which the dependence between the number of available resources and the volume of potentially fulfilled orders is described as nonlinear. For example, at low load, demand remains stable, but as the volume of performed transportation increases and the resource capacity limit is approached, a “saturation zone” appears, where new orders cannot be processed on time and efficiency begins to decline. (Andrejić & Pajić, 2024). That is why the microstrategy should include adaptive logistics tools that reduce the impact of fluctuations and make service more uniform throughout the year. Among such tools, the key role is played by the operational reservation of capacities and the creation of conditional load windows in forecasted peak periods with partial compensation due to reduced activity in the low season. Another tool is dynamic pricing, with which it is possible to adjust demand, redirecting it from peaks to off-seasons through a system of discounts or individual offers. The first and key direction of implementing the microstrategy is the formation of an operational model of transportation management, which should be based on the principles of optimal use of available resources: fleet, time, personnel and available information about orders, etc. In this aspect, route optimization acts not only as a tool for reducing fuel costs, maintenance and depreciation, but also as a means of increasing the productivity of the entire service chain (Fig. 1.). A small carrier, unlike a large logistics operator, does not have access to complex multi-level logistics systems, but it is able to manage routes as efficiently as possible at the local or regional level, using simple but dynamic algorithms for building delivery chains that take into account the density of orders, geographical proximity of points, traffic intensity and time constraints of customers. An additional element of the microstrategy should be the development of a service queue based on the principles of priority of regular customers, route profitability, as well as the duration of waiting for an order in the system. The introduction of such a mechanism allows for a controlled allocation of resources, avoiding chaos in decision-making and maintaining the stability of the logistics cycle even under conditions of overload or changing conditions. Yevhen Liestiev , 2(3) https://www.eujini.org.pl 28 Figure 1. Structural and functional model of implementing a microstrategy for positioning a small carrier in the external competitive environment Source: Developed by the author. Unlike large structures that can redistribute resources between regions or directions, small carriers are forced to look for solutions within a limited system, using their own potential as efficiently as possible. One such solution is the formation of a hybrid service model that involves the simultaneous provision of regular and one-time transportation. Standing orders provide the base load of vehicles and create the basis for forecasted cash flows, while one-time transportation allows to fill free windows in the logistics schedule, especially in the off-season. The optimal combination of these two forms of interaction allows to reduce the amplitude of fluctuations in transport loading (Makedon et al., 2025). External environment: influences from the transport services market, fluctuations in demand, actions of large logistics operators, access to orders, price parameters, technological innovations, and other factors that shape the operating conditions of logistics microbusinesses. Functional and organizational elements of the transportation process – production technologies: types of vehicles, transportation conditions; – structure: logistics lines, flight schedules; – production processes: transportation, performance control; – functions: cargo delivery, escort, reporting. Resource elements of the transport subsystem – objects of labor: cargo, transport; – personnel: drivers, technical staff; – technical means: trucks, control devices, GPS. Goals and strategies of the transportation management system Functional and organizational elements of transportation management: – functions: flight planning, load control, order processing; – structure: compact hierarchy, direct interaction with drivers and customers; – methods: adaptive planning, route optimization; – technologies: GPS monitoring, mobile platforms for dispatching; – management processes: operational decisionmaking, – schedule coordination. Resource management elements: – information: about demand, routes, cargo; – management personnel: dispatcher, manager, logistician. – technical means: software, means of communication. Subsystem being controlled (control object) Solutions – strategic decisions for transport optimization Control subsystem (control entity) Outputs – solutions Yevhen Liestiev , 2(3) https://www.eujini.org.pl 29 Another effective mechanism for increasing adaptability is the introduction of a “dynamic demand” model, in which the company actively influences the volume of orders by changing the terms of service. For example, during periods of low load, flexible prices, simplified ordering procedures or promotional services can be offered to attract additional demand, while during peak periods and vice versa, priority is given to serving customers with high margin potential. This approach allows maintaining economic balance without increasing the amount of fixed costs. Diversification of the customer base by industry affiliation should also be an appropriate practice. An enterprise that serves only one type of consumer (for example, only the construction sector or only agriculture) automatically becomes dependent on the cyclical fluctuations of this market. At the same time, a carrier that combines the service of diverse customers is able to mutually compensate for seasonal declines in one industry due to activity in another (Grzelakowski, 2025). In logistics, customer relations are increasingly moving away from unified procedures in favor of individualized approaches, and it is in this aspect that small carriers have a unique advantage over large players, which usually operate within the framework of rigidly formalized contracts. The practical implementation of the positioning microstrategy involves the formation of alternative mechanisms of interaction that can increase customer loyalty, reduce the likelihood of losing them and create the effect of long-term partnership. One of the most effective such mechanisms is the conclusion of individual agreements that allow adapting the terms of cooperation to the needs of each specific customer (Petrukha et al., 2022). Another tool is the use of short contracts, which are concluded for a limited period of time with the possibility of automatic extension or adjustment of conditions. For a small carrier, such a model is convenient in that it will help in the flexible formation of a portfolio of orders, without limiting itself to the fixed conditions characteristic of large long-term contracts (Table 1). Table 1. Comparison of Report Characteristics for Different Audiences in Agile Processes Direction Description Tools Advantages Limitation Optimization of the operating model Formation of an effective transportation management system based on optimal use of resources (fleet, time, personnel) Route optimization, delivery chain building algorithms, taking into account order density, geographical proximity, traffic, time constraints Reducing fuel, maintenance, depreciation costs; increasing logistics chain productivity Limited access to complex logistics systems; dependence on local/regional level Adaptive demand management Impact on order volume through flexible pricing and adaptation to seasonal fluctuations Dynamic pricing, promotional offers, simplified ordering procedures in the offseason, priority for highprofit customers during peak periods Flattening the demand curve, maintaining economic balance, attracting additional customers The need for accurate demand forecasting; risk of losing customers due to price increases during peak periods Flexible planning Prompt adjustment of transportation schedules depending on external and internal factors Reservation systems, floating service windows, quick rerouting Meeting customer expectations, avoiding inefficient transport loading High need for coordination and information systems for rapid response Formation of a hybrid model Combination of regular and one-off transportation for stable fleet loading Customer portfolio with opposing logistics cycles, capacity reservation during peak periods Forecasted cash flows, reduction of load fluctuation amplitude Difficulty in balancing between regular and one-time orders Personalized customer interaction Creating conditions for customer loyalty through personalized approaches Individual agreements, flexible schedules, special rates, short-term contracts with the possibility of extension Increasing customer loyalty, creating longterm partnerships, flexibility in forming an order portfolio High need for customer relationship management; risk of over-reliance on individual customers Source: Systematized by the author. When resetting the microstrategy of positioning a small carrier, there is a need to accurately forecast the behavior of demand for transport services, taking into account the possibilities of influencing it by the carrier itself through management decisions related to the scale of activity, quality of service, Yevhen Liestiev , 2(3) https://www.eujini.org.pl 30 speed of response, and route flexibility. Fig. 2 shows an analytical model that describes the dependence of demand (C) on the efforts made by a small transport enterprise, conventionally designated as the level of influence M, in a broad sense – this is a set of actions that shape the perception of the enterprise as a reliable service provider in the market. Figure 2. Model of dependence of demand for small carrier services on the level of operational activity Source: Developed by the author. As can be seen from the graph, the demand function varies from the minimum guaranteed demand value (C 0), which is a stable base even with a passive market presence, to the maximum market capacity (E), which the enterprise cannot exceed under certain conditions. In the initial zone of the curve (up to point t) the so-called area of demand insensitivity (zone 1) is fixed, where the carrier's efforts do not give a tangible result in attracting new orders. This is due to low recognition, lack of reputation and lack of a stable customer base. Only after overcoming a certain threshold of action do enterprises begin to have a noticeable impact, and the zone of effective demand growth (zone 2) begins, which lasts until the point of marginal efficiency (n) is reached. In this range, the growth of the activity of a small carrier leads to a gradual expansion of the volume of orders, stabilization of income and creation of a basis for the formation of long-term relationships with customers. After this, the saturation zone (zone 3) begins, where further increase in activity does not lead to a proportional increase in demand, as the market exhausts its potential or large players dominate in key segments. Arrow 4 in Fig. 2 illustrates the possible limit of achievable demand for a small business under existing constraints (Johnson et al., 2025). In the case when a transport enterprise sets a goal to increase overall financial efficiency by increasing demand for its services by a certain value ΔCм, it should operate within zone 2, where the greatest return on invested efforts is ensured. This approach requires systematic adjustment of internal processes: optimization of logistics routes, reduction of downtime, accurate planning of flights, which allows ensuring an increase in demand by the target value Δ P с, as shown in Fig. 3, where there is a conditional shift of the demand curve upwards, i.e. the enterprise approaches the upper limits of market potential. Figure 3. Model of dependence of demand for small carrier services on the level of operational activity Source: Developed by the author. С0 1 2 3 Е С М 4 С0 1 2 3 Е С М 4 Yevhen Liestiev , 2(3) https://www.eujini.org.pl 31 If there is cyclical demand behavior (seasonality, periodicity of large orders, dependence on the agricultural or construction cycle), a small transport company can smooth out these fluctuations by taking measures to increase the stability of service, reliability of the transportation schedule and versatility of its transport fleet (Pajak et al., 2020). This allows to translate the unstable demand curve into a relatively constant position, which is reflected in Fig. 3, where the new position of the curve demonstrates more predictable and stable dynamics. In the final part of the model (Fig. 4) the function of the forecast production program is considered, which depends on the budget of the enterprise's logistics resources, including operating costs, the volume of the available fleet, the number of personnel and other structural parameters, conditionally combined into the indicator B mi - the budget for ensuring activities in the i - m direction of services. Figure 4. Functional model of the forecast production program of a small carrier depending on resource provision by areas of logistics activity Source: Developed by the author. Then the forecast production program is a function that takes into account not only the expected demand, but also the real capabilities of a small carrier to meet it without losing service quality or violating logistical obligations. To achieve a dynamic balance between the volume of orders that a small transport company is potentially able to serve and its limited resource capabilities, in particular the number of transport units, staffing, as well as time and route restrictions. Ensuring such a balance not only avoids situations of vehicle downtime or, conversely, when resource overload with the risk of disruption of logistics operations, but also forms the basis for sustainable market behavior, which is a guarantee of trust from regular customers. Careful planning of the services provided, taking into account the dynamics of demand, allows to minimize the costs associated with the unpredictability of orders and increase operational efficiency, especially during periods of peak load or seasonal market unevenness (Mageto, (2022). To further present this problem, the authors will introduce the following conventions that will allow us to formalize the process of constructing a function of the forecast production program of a small carrier, which takes into account the available resource supply, transport capacity, and service provision schedule within the framework of the chosen positioning strategy. - the total volume of transportation orders received before the beginning and during the planning period ; - volume of transportation for the planned period of time ; - the initial volume of available transport resources for fulfilling orders in the planning period; – total available logistics capacity of a small carrier in the analyzed period, . Ni t Bмі Yevhen Liestiev , 2(3) https://www.eujini.org.pl 32 Dependence of the operating effect obtained at the end of period t on the size of orders for the received shipments and the planned quantity of finished products is determined by the function : , if , (1) , if , (2) where , are functions that determine the effect in cases of lost profit and availability of orders, respectively for transportation; - expected profit from performing one transportation under conditions of optimal (normative) vehicle loading - losses associated with vehicle downtime due to excess supply of services within one planning period, calculated per unit of potential transportation; - lost profit from unfulfilled transportations with existing demand due to limited transport capacity; - losses caused by inefficient use of the fleet due to downtime or excessive resource load. At the same time: , if , , if , where – the number of losses per unit of transportation caused by transport downtime; - the number of losses per unit of transportation arising from overloading of vehicles or exceeding operating capacity. volumes can be viewed as realizations over time periods of random variables characterized by corresponding probability density functions and mathematical expectations that can be found on the basis of retrospective information on the volumes of transportation orders . If the future demand volume for the future time period t is known exactly, then , there are no losses, . If the future demand volume for transportation is a random variable , then the future demand is often estimated by the mathematical expectation , and the predicted effect is estimated by the value =tt Ed  . In this case, the value is mistakenly considered to be the exact value of future demand, rather than its most probable value. This procedure for selecting transportation volumes does not take into account that a change in demand per unit in a certain direction (larger or smaller) can lead to a much greater decrease in the operating effect =tt Ed  than a change in demand per unit in the opposite direction. In other words, in the general case, the value =tt Ed  does not correspond to the mathematical expectation of the operating effect under the selection condition .