Profit Of Retailer Research Articles

Inventory Decisions Considering Returns in Omni-channel Retailing

Omni-channel retail is a new model that is achieved by integrating online stores and offline physical stores. The inventory decision problem considering returns under omni-channel retail is studied in two cases: considering same-channel returns under omni-channel retail and considering cross-channel returns under omni-channel retail. Based on the consideration of consumer returns and resale of returned products, the newsboy model is used to construct inventory decision models with the goal of maximizing retailer profits and analyze the models. Numerical analysis shows that the online store return ratio and the cross-channel return ratio have a significant impact on the inventory and profit of the retailer's offline physical stores and online stores. In particular, when the cross-selling profit is large, the cross-channel return ratio increases, and the retailer's profit increases accordingly, but the retailer's profit may decrease with the increase of the online store return ratio.

Retailer-Manufacturer Partnerships in E-Commerce: Dual Product Strategy and Market Share Dynamics

A new practice among online retail platforms, e.g., Amazon and Wayfair, is to offer their own private label product and a substitutable exclusive manufacturer product. We employ a game theoretic approach to examine conditions under which a retailer and a manufacturer find it optimal to enter into such a partnership. Our analysis reveals that a retailer finds it profitable to partner with a manufacturer with one of two profiles. The first is a manufacturer with low unit production and holding costs and large capacity, and the retailer gives the manufacturer most of the market share. In this case, the retailer uses a low private product price and marketing effort to pressure the manufacturer to set a low exclusive product price, which increases the manufacturer's revenue and the retailer's fees. The second is a manufacturer with a large consumer base, high unit production and holding costs, and small capacity. For this profile, the retailer takes most of the market share by offering a low private product price, and the manufacturer is unable to counteract the retailer's low private product price and marketing effort. The partnership results in a lower price when the marketing effort is costly and the retailer relies on private product price, intensifying price competition. Under some conditions, the retailer's profit may decrease in his share of the manufacturer's revenue. Also, the retailer may increase the marketing effort and decrease the private product price, not to take market share, but to pressure the manufacturer to decrease price.

Biomass supply chain coordination considering government subsidies and corporate social responsibility

PurposeThe purpose of this paper is to investigate the impact of various decision-making approaches and government subsidies on supply chain performance, aiming to enhance the profits of disposal firms and retailers as well as to improve social welfare.Design/methodology/approachIn this paper, a two-echelon biomass supply chain composed of a disposal firm and a retailer is developed. Firstly, considering the effects of government subsidies, we analyze biofuels prices, corporate social responsibility levels, social welfare and supply chain profitability under centralized and decentralized decision-making scenarios, respectively. Furthermore, we assess how subsidies influence pricing, market participation, profitability and social welfare. Secondly, we propose a revenue sharing–cost sharing contract to enhance the profits of the disposal firm and retailer. Thirdly, we extend the supply chain to a disposal firm and two retailers and explore the impact of competition intensity on corporate decision-making behavior. Finally, numerical analysis is conducted by taking one biomass energy firm as an example to support the results.FindingsOur research finds that (1) Equilibrium strategies under the centralized decision-making scenario are greater than those under the decentralized decision-making scenario. Centralized decision-making can increase market demand and consumer surplus. (2) Government subsidies can promote corporate social responsibility levels, despite causing a slight increase in retail price for biofuels. When market competition intensifies, companies usually reduce their investment in CSR, and this trend is particularly pronounced in the absence of subsidies. (3) In both the decentralized and the centralized decision-making scenarios, increasing conversion rates and the CSR coefficient can significantly increase the overall profitability and social welfare.Research limitations/implicationsA three-echelon biomass supply chain involving collection station, disposal firm and retailer can be studied in the future.Originality/valueBy examining the effects of subsidies on CSR engagement and market outcomes, our study contributes valuable insights into policy design for promoting sustainable practices in biomass industries.

Green electricity product menu design for retailers without knowing consumer environmental awareness

Adverse selection problem due to asymmetry of consumer environmental awareness (CEA) could reduce electricity retailer's profit and obstructs renewable energy (RE) consumption. This study analyzes mechanism design problem of retailer constricted by RE consumption quota to incentive consumers display true CEA in competitive retail market. Based on principal-agent theory, we develop an extended principal-agent model with the addition of an RE consumption quota constraint to design a green electricity product menu which includes the green level, the price and electric quantity. Influence of information symmetry and quota setting on product attributes, retailer's profit, consumer utility, RE consumption is analyzed, and results show that: (1) Compare to symmetric information, under asymmetric information, green level of product provided to consumers with CEA (denoted as C1) distorts upward, information rent is greater than zero when quota is large, while green level of product provided to consumers without CEA (denoted as C2) distorts downward, with no information rent. (2) Under asymmetric information, unit environmental premium (UEP) of green electricity positively relates to proportion of C1, CEA level, and incremental WTP, and reaches the maximum value at a certain quota. (3) Under asymmetric information, retailer's profit and RE consumption positively relates to proportion of C1, and CEA level. (4) Under asymmetric information, quota difference could contribute to improve retail service quality under competitive retail market, and RE consumption elevation.

National brands versus store brands: retailer fight against national brands to improve store brands via a dynamic discount pricing strategy

Today, there is a lot of competition between competitors in the market of different products. The level of complexity of relationships and behavior of active players in the market has also increased. So that a manufacturer and retailer work together to increase the profit of the supply chain through the sale of products. On the other hand, the retailer and the manufacturer as competitors are competing with each other to sell more of their products. This issue has increased the complexity of the relationship between retailers and manufacturers. This study aims to explore how retailers can strengthen the self-introduced store brand (SB) and resist the pressures of manufacturers by using dynamic discount pricing (DDP) strategy. Numerical examples are proposed to clearly explain the validity and applicability of the model. Based on the managerial insights developed by analyzing the model's results, we evaluated the influences of DDP strategy on the retail prices and demands of national brands (NB) and SB and the profit of the retailer and the manufacturer. We found that discounts on the manufacturer's product by the retailer increase the demand for both NB and SBs. An increase in demand leads to an increase in the profits of manufacturers and retailers. However, the increase in the manufacturer's profit does not compensate for the decrease in his market share. In other words, the introduction of an SB always causes damage to the manufacturer, but the amount of damage depends on various factors. These findings offer manufacturers and retailers useful insights and help them adopt effective marketing strategies.

Price and carbon emission reduction technology competition in the electricity supply chain based on power structure

This study considers the research on electricity pricing and carbon reduction technology decisions of electricity supply chain enterprises under different power structures, and constructs a two-level electricity supply chain game model composed of two electricity producers and a single electricity retailer. By comparing the equilibrium solution results, the main research results are as follows: (1) In the market structure where electricity producers and electricity retailer make decisions at the same time, electricity producers are more willing to invest in low-carbon technologies and increase carbon emission reduction. The electricity retailer also set the lowest electricity prices at this time, and electricity demand is the highest. (2) In the case of the Stackelberg game for electricity producers, the wholesale electricity price is the highest, and the electricity producers obtain the most profits. In the case of the Stackelberg game for electricity retailer, the electricity price is the highest, and the profit of the electricity retailer is the highest. (3) In the market structure dominated by electricity retailer, the electricity price is the highest, and the electricity producers reduce the investment in carbon emission reduction technology after observation; the carbon emission reduction intensity is the least, and the electricity demand is also the least. (4) With the increase of price competition coefficient, the carbon emission reduction intensity, electricity demand, electricity producers and electricity retailer profit increase. However, as the competition coefficient of carbon reduction technology increases, these equilibrium solutions decline. We verify the above conclusions using multi-agent simulation.

Robust pricing and inventory decisions in ship‐from‐store omnichannel operations

AbstractThis work studies the deployment of the ship‐from‐store omnichannel strategy and the pricing and inventory decisions for an online retailer. Robust optimization models are constructed for the online‐only and the ship‐from‐store modes under a budgeted uncertainty set. The ARIMA model is used to predict the parameter values of the budgeted uncertainty set using historical demand data. The closed‐form optimal solution for the online‐only mode is obtained. The robust counterpart model for the ship‐from‐store mode is converted to a mixed integer quadratic programming model. Numerical studies are conducted to validate the theoretical results and to verify the effectiveness and practicality of the developed robust optimization solution approach. The results show that adopting a ship‐from‐store strategy may hurt the retailer's profit if a significant proportion of consumers are time‐sensitive with high travel cost. The ship‐from‐store strategy is optimal if it significantly boosts market growth.

Effect of Governmental Subsidies on Green Energy Supply Chains: A Perspective of Meteorological Disasters

The energy sector, serving as a pivotal propellant within the macroeconomic framework, finds its production, distribution, and consumption aspects considerably influenced by climatic variations. In this study, a two-tier Stackelberg model for the green energy supply chain is developed, which is employed to analyze the profit disparities between suppliers and retailers both in the absence and presence of meteorological disasters. Furthermore, the research delves into the optimal supply chain strategies under three distinct scenarios in the context of meteorological disasters. A comparative analysis is conducted to examine the decision-making variances and the shifts in the interests of each supply chain participant under these scenarios. The findings reveal two critical insights: First, meteorological disasters detrimentally affect the environmental friendliness of energy products, as well as the profits of both retailers and suppliers. Second, the selection of the optimal strategy varies depending on the evaluation criterion used. When product greenness is the metric, subsidies aimed at promoting sales costs emerge as the superior strategy. Conversely, for retailers and suppliers, subsidies that target the environmental friendliness of energy products prove to be the most effective. Based on the conclusions, the paper also makes recommendations for governments and companies.

Optimal strategies in electric vehicle battery closed-loop supply chain considering government subsidies and echelon utilization

This study examines an electric vehicle battery closed-loop supply chain including a battery manufacturer and a retailer, with a focus on echelon utilization and remanufacturing of waste electric vehicle battery. Optimal pricing strategies and technological effort decision of the supply chain members are derived based on a Stackelberg game model. Three government subsidy policies are considered to promote recycling and reuse of waste electric vehicle batteries, namely, no subsidies, production research and development (R&D) subsidies and recycling subsidies, respectively. Results show that both echelon utilization and recycling subsidies can notably contribute to recycling rate of waste electric vehicle batteries. While echelon utilization boosts the profit of retailer and the whole supply chain, it may have a negative impact on manufacturer's inclination to remanufacturing and its profit. Subsidies for production research and development are preferred by the supply chain and its members from the profit-oriented perspective. Further analyses are conducted under hybrid strategies: hybrid government subsidy policy and hybrid recycling mode. Results show that hybrid strategies could significantly increase the demand and recycling volume, thus positively affecting the profitability of the entire closed-loop supply chain. Our study comprehensively considers the game relationships among manufacture and retailer, enhancing the efficiency of recycling and profitability while also providing a theoretical basis for the government to formulate reasonable subsidy policies.

Should the pricing or advertising decision come first in a supply chain with a network externality?

Purpose This paper aims to study how the timing of these decisions affects the total profit and the individual profits of the two agents. Design/methodology/approach This paper study a supply chain for a network good where there is a manufacturer and a retailer. The manufacturer determines its wholesale price and its share in the retailer’s advertising cost while the retailer decides the retail price and the advertising cost. Findings This paper finds that a stronger network externality leads to higher prices and higher advertising efforts. This increases the profits of both manufacturer and retailer, but the manufacturer’s share of advertising costs depends on the order in which the supply chain enterprise make their decisions, the strength of network externality and the effect of advertising determines which decision timeline results in a higher price and greater advertising effort. The manufacturer prefers the price decision to be made before the advertising decision, while the retailer prefers these decisions to be made simultaneously. Research limitations/implications Although this paper studies the price and advertising decision-making order preferences of channel members based on network externalities, this research can also be expanded from the following aspects based on network effects. First, network externality affects advertising cooperation between both parties in the situation such that the pricing power of retail prices is transferred from the retailer to the manufacturer and the retailer relies on revenue sharing (revenue sharing contract, nonwholesale price contract. Second, the manufacturer dominates the issues in the supply chain, but in reality, a retailer can also be the dominator or there are no dominators (Nash equilibrium). Finally, it is possible to consider pricing and advertising decisions in situations where two manufacturers or retailers compete. Practical implications When the price is reasonable, advertising investment is the main determinant of product sales. The greater the intensity of network externalities the more retailers will be willing to invest in advertising. An increase in the intensity of network externalities may not necessarily enhance manufacturers’ motivation or cooperative advertising, but it depends on the decision-making sequence. The strength of network externalities determines the decision-making sequence preferences of supply chain channel members whose preferences vary leading to conflicts of interest. Originality/value The impact of cooperative advertising or decision sequence on corporate decision-making has not been considered. To fill this gap, the paper integrates network externality and supply chain cooperative advertising models, focusing on the impact of network externality on pricing and advertising decisions, as well as on the sequence of decisions.

Revenue forecasting in smart retail based on customer clustering analysis

Understanding your customers is among one of the most important strategies to boost retail profit. In this research, we propose a WiFi-based sensing method to analyze customer behaviors. The monitoring of customer behaviors may lead to revenue growth. Specifically, the strategy is focused on understanding and grouping customers’ behaviors in which we track customers who share similar visiting patterns through WiFi sensing. Accordingly, we can have group-based prediction done for customers who own similar behaviors. We extract customers’ visiting patterns including the customers’ Service Set Identifier list and related information. After all, the proposed system is realized in a cafeteria place where we have the deployed WiFi access points continuously collect data over a time horizon of three months to serve as the inputs for data analysis. The data samples include the number of customers’ devices, number of products and revenue amounts. The dataset also integrates group information and weather conditions. We adopt several machine learning methods including Support Vector Regression and Random Forest for model induction. We conduct these models in terms of three main prediction tasks consisting of coffee shop’s revenue, the number of products, and the number of customers’ devices for evaluation. Furthermore, considering these predictions, we separate between the staying-in and to-go parts. Based on the experiment result, customers’ group information helps, as well as weather conditions. Overall, we can achieve the best prediction result when both the group information and weather conditions are included where we can enjoy as good as 6% to 10% in MAPE.

Optimal Pricing and Retailing Strategy for an Assembled Product Manufacturing–Remanufacturing Process under Carbon Emission Regulations and Autonomation

Online-to-offline (O2O) retailing offers unique opportunities for customizable assembled products with spare parts. Customers can browse and configure their desired product online, selecting from various components. Imperfect production, where a certain percentage of products have defects, can be amplified in the manufacturing system. Stricter carbon emission regulations put pressure on manufacturers to minimize waste. This creates a tension between discarding imperfect products, generating emissions, and potentially offering them at a discount through the O2O channel, which could raise quality concerns for consumers. In this study, an imperfect single-stage production process is examined, incorporating manufacturing–remanufacturing within a single stage for assembled products containing various spare parts. The study explores an investment scenario aimed at enhancing the environmental sustainability of the product. Additionally, two carbon emissions regulation strategies, specifically carbon cap-and-trade regulation and carbon taxation, are evaluated for their effectiveness in mitigating carbon footprints. The identification of waste, particularly in the form of defective items, is achieved through automated inspection techniques. The demand for spare parts associated with the assembled products is intricately linked to the selling prices set across diverse channels. Finally, the total profit of the manufacturing system is maximized with the optimized value of the selling prices, order quantity, backorder quantity, and investments in autonomated inspection, setup cost, and green technology. Numerical illustrations show that system profit was optimized when the defective rate followed a triangular distribution under carbon cap-and-trade regulation and when green technology investment helped to enhance retailer profit by 18.12%, whereas autonomated inspection increased retailer profit by 10.27%.

The effect of price and assortment of local products on store performance: An agent‐based modelling approach

AbstractRetail distribution is essential for the growth of markets for local food. While online direct‐to‐consumer and local food hubs are becoming more sophisticated, the largest market for local foods remains the traditional intermediation (retailing) sector. We develop an agent‐based model to simulate the expansion, growth and profitability of retailers offering local foods across a landscape populated by consumers and competing retailers. We design a series of experiments to examine how changes in prices and assortment that include local and non‐local options in the fresh produce category impact store market share and profitability. We validate the model, and conduct our experiments, using household fresh produce expenditures data from a retail food‐delivery business in the Mid‐Atlantic region of the US. We find that retailers offering a larger assortment of local foods are able to sustain higher basket‐average retail prices and exhibit higher long‐run profits in comparison to retailers that do not carry local options. These results underscore the importance of local foods in a food retailer's price and assortment strategy. The key implication is that retailers need to be conscious not only of the breadth but also of the quality of their assortment in their pricing strategies.

Dual-channel decision models for the transnational supply chain considering strategic inputs and compensation

Based on a transnational dual-channel supply chain consisting of the domestic manufacturer and retailer, this paper constructs four models, namely, the without tariff model, the tariff model, the retailer’s strategic inputs model, and the manufacturer’s compensation model, to investigate the impact of the tariff imposing on supply chain decisions, the effect of the retailer’s strategic inputs to hedge against tariffs, and the incentive effect of the manufacturer’s compensation. The results show that the tariff imposed by the foreign government leads to higher product prices and lower sales volumes, resulting in welfare losses for foreign consumers. When the domestic retailer makes strategic inputs, the prices of products in the foreign market decrease and the sales volumes increase, which increases the profits of the domestic retailer and manufacturer and improves the welfare of foreign consumers. The equilibrium solutions of the models also show that the manufacturer has an incentive to compensate the retailer for its strategic inputs; when the manufacturer compensates for the retailer’s strategic inputs, the profit of the retailer and the manufacturer will be improved again, and thus, the whole supply chain will achieve Pareto improvement.

Research on pricing strategies for competitive green supply chain based on corporate social responsibility

With the increasing public awareness of environmental protection, corporate social responsibility has become an important component of sustainable development and competitive advantage for many enterprises. Although there are many studies on corporate social responsibility in the supply chain, there is still a lack of research on the impact of corporate social responsibility on various decision-makers in the competitive green supply chain dominated by upstream enterprises. Therefore, taking into account the greenness and corporate social responsibility, the paper proposes three Stackelberg game models with the two-echelon supply chain consisting of two competing manufacturers and one socially responsible retailer. We develop a series of propositions and corollaries to determine the optimal solutions and offer some managerial insights. The main novelties and contributions of the paper can be demonstrated in two aspects. First, the paper simultaneously considers the impact of competition intensity and CSR level on wholesale prices, retail prices and greenness level. Second, the paper discusses the impact of two manufacturers with different market positions investing in green products on the profits and utility of supply chain members. Numerical illustrations prove that the level of corporate social responsibility is negatively correlated with retailer profitability and the retailer achieve the highest profits when sub-dominant manufacturer produces green products.

A pool-based electricity retail markets integrating renewable energy sources and electric vehicles in the presence of demand response program and conditional value at risk to enhance energy security

In restructured power systems, energy security has become a critical concern, driven by changes in laws and regulations and underscored by a defensive approach implemented by the independent system operator. This alignment highlights a strong interdependence between energy security, energy supply, and the economic aspects of energy management. The paper explores how consumers energy supply in restructured systems can be managed through Demand-Side Management (DSM) and Demand Response (DR) programs, considering economic efficiency and risk in scenarios that include Renewable Energy Sources (RES), suitable storage systems, and electric vehicles (EVs). An energy security index is introduced to evaluate the impact of DR programs on both electrical and thermal energy, considering the economic risks involved. A hybrid pool-based electricity retail market approach is utilized to optimize energy security, supply, and consumption. The significant roles of RES, storage systems, and EVs are highlighted in this context. Economic and environmental optimization is achieved using the Conditional Value at Risk (CVaR) method, facilitating strategic decision-making under varied risk conditions. The energy supply security is further analyzed in the presence of electricity market retailers, exploring different pricing strategies. A Mixed-Integer Programming (MIP) model, implemented in GAMS software with the CONOPT solver, is used to examine pricing methods such as Time-of-Use (TOU) and real-time pricing. Findings reveal that DR programs lead to substantial increases in retailer profit and energy supply security value, with real-time pricing showing a significant 23.5 % increase in energy supply security value and a 24.5 % increase in retailer profit compared to fixed tariff pricing.

Pricing strategy based on a stochastic problem with barter exchange under variable promotional effort for a retail channel

Barter exchange platform gains popularity as an effective trade exchange strategy to minimize the vast use of paper money. In retail management, the application of the barter platform is growing because of cashless trade. It allows a retail enterprise to trade unused products in exchange for other assets purchased by reducing the actual purchase of assets. In this context, the study analyzes a stochastic model of a barter exchange problem under a retail channel. It investigates the barter exchange policy in three different models: conventional newsvendor model without barter exchange, with barter exchange, and with barter exchange with promotional effort and emissions level. The market demand for products is considered random and random with deterministic variables for three types of models. Stochastic models are solved in two different ways: with and without probability distribution functions of the random market demand. For maximization of the retailer's profit, the proposed framework obtains optimal decisions on ordered quantity, retail price, promotional effort, and emissions level. Five examples are tested and numerical results show that the barter exchange policy is more profitable than a traditional newsvendor model. A combination of stochastic and deterministic variable demand provides 34.31% more profit than a stochastic demand. Sensitivity analysis, discussions, and managerial insights are provided in detail on optimal decisions.

Return strategies and channel pricing in omni-channel retail considering heterogeneous customer perceptions

As Internet technology advances, the retail industry is increasingly adopting omni-channel operational strategies. This research delves into the interplay between return losses and customer perceptions of online products, and how these factors influence profit-maximizing omnichannel retailers’ optimal return strategy and channel pricing. Previous studies have primarily focused on cross-channel aspects and have not thoroughly explored the impact of return loss on profitability in an omni-channel context. The study assumes that profit-maximizing retailers allow consumers to choose their purchase channels based on perceived utility of different channels, while adhering to the retailer’s stipulated return strategy. To this end, we introduce three distinct return strategies (returning products via the original purchase channel, offline return, and online return) for omni-channel retailers. We aim to identify the most profitable return strategy by considering diverse return losses associated with each channel and consumers’ perceptions of online products. Our analysis identifies scenarios in which a particular return strategy either boosts or reduces retailer profit, thereby facilitating optimal channel pricing decisions. Our findings reveal that customers’ purchasing channel selections are affected by their perception, retailer’s return strategy, and net return loss. We also find that no matter what kind of operation scenarios the retailers adopted, the retailers should let all customers return to the online channel to generate maximum profit when the difference between the retailer’s online and offline net return loss is less than the difference between the customer’s online and offline return hassle cost. Conversely, an offline return strategy proves more profitable. Our findings are supported by numerical simulations, guiding omni-channel retailers in making informed decisions regarding return strategies and channel pricing.

Implications of risk-averse manufacturer on coordination of green supply chain with mixed carbon policies

PurposeThis paper intends to address the decision-making and coordination of green supply chain (GSC) considering risk-averse manufacturers under mixed carbon policy.Design/methodology/approachThis paper focuses on a GSC consisting of a manufacturer and a retailer, in which the manufacturer is risk-averse (R-A). This paper employs Stackelberg game theory and mean variance analysis to assess the pricing decision-making process under various scenarios. Furthermore, cost-sharing contracts are introduced to coordinate the GSC.FindingsThe research results suggest that the green level of the product and the profit of the GSC under a centralized scenario are higher than those under a decentralized scenario, while the retail price is lower. Under the decentralized scenario, the green level of product, wholesale price and manufacturer’s profit in the R-A scenario are lower than the values in the risk-neutrality scenario, while retailer's profit is higher. In addition, when a cost-sharing contract is utilized for coordination in the GSC, it can lead to Pareto improvement, regardless of whether the manufacturer makes risk-neutrality or R-A decisions.Originality/valueThis research provides a deeper understanding of GSC decision-making and coordination strategy under mixed carbon policy with consideration of R-A from a theoretical perspective and provides decision support for enterprises to choose strategies in practice.

USING ECONOMETRIC MODELS FOR MANAGING DISTRIBUTION PROCESSES

Introduction. The constant increase in competition and rapid changes in market conditions compel various business entities to seek more efficient ways to manage the distribution of goods. In this context, econometric models become an indispensable tool for analysis and forecasting, enabling informed decision-making, optimization of logistics processes, and cost minimization. Objective. The aim of this article is to substantiate effective econometric models for managing the distribution of goods to optimize supply processes, sales, and maximize profits for manufacturers, retailers, and other participants in distribution channels. Methods. The theoretical and methodological basis of the research consists of works by domestic and foreign scientists on the implementation of econometric models for managing business processes, including distribution. The informational basis includes scientific, economic, and reference literature, works of leading domestic and foreign scientists, methodological materials, information portals, and periodicals of Ukraine. A set of methods and approaches were used: system analysis – for studying the role and significance of econometric models for goods distribution and identifying their features; methods of analysis and synthesis – for analyzing and systematizing econometric models and determining the advantages and limitations of their application for goods distribution. Results. The study investigates the role and significance of econometric models for goods distribution. It examines how these models can become a key tool in solving optimization tasks, adapting to changing market conditions, and ensuring competitiveness in a world where distribution strategies turn into strategic advantages. The advantages and limitations of applying such models are identified: simple linear or nonlinear demand models; time series autoregressive model ARIMA; exponentially smoothed model ETS; transportation problem model; Vehicle Routing Problem (VRP); Traveling Salesman Problem (TSP); orienteering problem; conjoint analysis. Conclusions. Based on a comparative analysis of the key aspects of using econometric models for goods distribution, their specific aspects depending on the implementation of particular tasks and needs of the business entity are detailed. The main advantages of applying econometric models in distribution are highlighted, primarily providing the ability to effectively consider a large number of factors affecting distribution processes, along with certain limitations of their use. Among the main benefits are more accurate demand forecasting, which allows for optimizing inventories and supply chain management costs, as well as strategies for warehouse placement, route selection for delivery, etc.