Demand Volume Research Articles

Location and two-echelon inventory network design with economies and diseconomies of scale in facility operating costs

Most existing facility location and network design models assume the facility cost as either a fixed cost term or a linear/concave function of the volume of demand assigned to a facility. In particular, a concave cost function implies decreasing marginal cost and exhibits economies of scale. However, when the assigned demand volume exceeds a certain level, diseconomies of scale may occur due to facility congestions, overuse of resources, increasing operational complexity, and so on, leading to a convex cost function with increasing marginal cost. This paper studies a warehouse–retailer network design problem, which simultaneously optimizes the warehouse locations, the warehouse–retailer assignment, and the multi-echelon inventory replenishment policy to minimize the total cost, including the warehouse location and operating costs, the inventory replenishment cost, and the transportation cost. In this paper, the warehouse operating cost is defined as a general function of the volume of demand assigned to a warehouse, which could be concave first due to economies of scale and then convex due to diseconomies of scale. We formulate this problem as a set-covering model and propose a column generation algorithm to solve its linear relaxation. The pricing problem of the column generation process, although formulated as a nonlinear mixed integer program, has nice structural properties and can be solved efficiently by a branch-and-bound method. To validate the effectiveness and efficiency of the proposed column generation algorithm, we conduct numerical studies based on randomly generated instances. Numerical results also demonstrate the impact of economies and diseconomies of scale on network design decisions and warehouse operating cost.

Heuristics for setting reorder levels in periodic review inventory systems with an aggregate service constraint

Inventory managers are responsible for the trade-off between inventory holding costs and customer service. In this paper we consider a periodic review multi-item inventory system with exogenous lot-sizes and backordering. The objective is to minimize the total inventory holding costs subject to the constraint that the aggregate fill rate should be at least equal to a target level. The aggregate fill rate is a weighted average of the fill rates of all items in the assortment. We consider three ways of defining this aggregate fill rate: using generic weights, weights based on the average demand (volume) or weights based on the average (monetary) turnover. We show that the definition of the aggregate service can have huge effects on the performance of the system. So, inventory managers should be very careful on which definition to apply. We also derive four heuristics to determine the reorder levels for all items. One heuristic is very generic and can be applied to many problems including multi-item multi-echelon inventory systems and systems with a constrained aggregate ready rate. Since multiple assumptions made to derive the heuristics are common assumptions made in the literature, we first test the accuracy of these approximations using simulation. Next, we evaluate the heuristics based on data from a large international reseller. The heuristic based on the most accurate approximation performs best, is close to optimal and very efficient. Savings compared to no service level differentiation are large (up to 28.7%) and depend on the definition of the aggregate service.

Resource allocation mechanisms for maximizing provider’s revenue in infrastructure as a service (IaaS) cloud

Infrastructure as a Service (IaaS) is a cloud computing service provided over the internet to facilitate the provisioning of various services such as storage, processes, etc. The provider in the IaaS market may offer some purchasing plans including: reservation, on-demand, and spot plans for its resources. As in real scenarios, demand volume for each plan is assumed to be a random variable with a given probability distribution. The provider maximizes its average revenue in the long run by optimal allocation of its resources among the plans. We formulate an Integer Linear Programming (ILP) model with a stochastic constraint, to determine the number of resources to be allocated for each plan in every time slot in the planning horizon. First, fixed prices are considered for each plan, then two mechanisms of Continuous Double Auction and Second Price Sealed Bid Auction are considered for reservations and spot plans, respectively, to obtain market-driven prices of the services. The Seasonal Weighted Moving Average method is used to predict the amount of demand in every slot. Finally, the proposed mechanisms are evaluated through simulations and the results confirm the effectiveness of the methods in maximizing the revenue and overall utilization of the available IaaS capacity.

Стратегии поведения промышленного предприятия на энергетических рынках как инструмент реализации принципа рационального поведения

To ensure the sustainability of their market, energy-intensive industrial companies need to address energy efficiency issues. Companies that are prepared for higher tariffs, structural changes in fuel and energy markets, and shortages of energy resources have a wider range of options for responding to new challenges posed by the external environment and reducing their risks. This challenge becomes especially relevant in the context of the development of closed-loop economy aimed at resource optimization, energy conservation, zero-waste production and business models based on maximum operational efficiency. This research aims to build a comprehensive view of the rational behavior of industrial energy consumers in an effort to maximize the benefits and potential of energy markets to reduce the cost of energy supply, increase the level of electrification of industrial production and use the opportunity of their own energy business, as well as identify the main strategies of manufacturing companies in the energy market and the conditions for their effective implementation. The article describes the basic principles of rational behavior, which serve as a basis for the effective implementation of various strategies (seller’s, buyer’s or combined strategy) for industrial enterprises. The connection between rational behavior and management of the energy market potential in the company, as a combination of technological, economic and organizational actions, performed by the energy consumer in the competitive market, and effective management of market risks is shown. Forms of off-grid power supply and conditions of their application in production were analyzed on the example of mini-CHP. The offered classification of behavior strategies of an enterprise at the power market allows making a rational choice among various variants of behavior corresponding to concrete marketing purposes of the company. The choice can be made by analyzing the technological features of production processes, determining the marketing goals of the company, checking the volume of demand and the structure of demand (supply) for the main products of the company, as well as the amount of energy needed for production. It has been shown that as smallscale generation technologies become more advanced, having an on-site energy source becomes a more attractive option. Along with the penetration of smart technologies into core production practices and the transition to a new energy paradigm, conditions are created for the integrated use of various resource reserves.

Diuretic Activity of Indian Medicinal Plant: A Review

Diuretics are commonly defined as drugs that increase the amount of urine produced by kidney. A precise definition is that diuretics are the agent which augment the renal excretion of sodium and either chloride or bicarbonate primarily, and water excretion secondarily. The term “saluretic” is sometime used to describe a drug that increase the renal excretion of sodium and chloride ion Diuretics are responsible for increase the rate of urine flow, sodium excretion and to maintain the volume and composition of body fluids in a various clinical Disorders. But drug-induced diuresis is very much beneficial in such type of life-threatening disorders like CHF, hypertension, renal failure, Liver cirrhosis and often pregnancy toxaemia.[1] Diuretics relieve pulmonary congestion and peripheral edema. This decreases cardiac workload, oxygen demand and plasma volume, thus decreasing blood pressure. Thus, diuretics play an important role in hypertensive patients.[2] Plant medicine is commonly used in the traditional treatment of some renal diseases, and many plants are reported to possess significant diuretic activity. The diuretic activity of a number of plants used in ethno medicine as diuretic agents has been confirmed in experimental animal. [3]The progress of a polyherbal formulation is a tough job because of the large number of different chemical compounds present in the different medicinal plants.

Application Of Saving Matrix Method In Determining 3 Kg Lpg Distribution Routes To Minimize Transportation Costs In. Pojur Real Madura

The transport route is a solution that minimizes the cost of distribution. The savings matrix method is the vehicle routing problem (VRP) method for obtaining an efficient route. The use of this method is to combine the destination points with the greatest distance savings and to take into account the volume of demand per destination. Then order the visits to the vehicle so that an efficient delivery route is obtained. This paper discusses the use of the savings matrix method in the determination of product delivery routes for PT Pojur Real Madura. At the end of the work, it turned out that this method showed that the route obtained was less than the original route, namely from 16 routes to 10 routes. Within a month, distance savings of 184 km or about 30 per cent were achieved, fuel savings of 61 liters or about 26 per cent were achieved, so that the use of the vehicle was reduced, which meant that costs could be minimized.

Обзор мирового рынка железной руды за 2019–2020 годы

Preliminary figures of global iron ore and steel production in 2020 show a slight decline. The article reviews iron ore production by global companies (Vale, Rio Tinto, BHP, FMG, Anglo American, etc.) in 2019 and 2020, as well as production figures by the leading steel producing countries (China, India, Japan, Russia, USA, South Korea) in 2020. Iron ore imports and exports are also analyzed. It is noted that the global iron ore exports had increased by around 43% over the previous decade, however, they went down by 1.7% in 2019, and this decline in exports continued in 2020. Australia is the largest iron ore exporter with a market share of 55%; this share increased by one percentage point in 2020 compared to the previous year. Green-field projects by global producing companies are presented in Brazil, Australia and other countries. A conclusion is made that despite a 3.5% decline in the global economy forecast by the International Monetary Fund in 2020, it is possible to acknowledge that the iron ore market is well balanced. However, if steel demand and steel production volumes increase unexpectedly and some of the planned new mines are not commissioned, the surplus can quite promptly turn into a deficit. In the long term, the plans to produce steel without using fossil fuels, without coke and therefore without CO2 emissions, could revolutionize the iron ore market and increase the demand for products with a high iron content. Источник: https://mining-media.ru/en/articles/original-paper/16396-iron-ore-market-report-2019-2020

Optimizing freight rate of spot market containers with uncertainties in shipping demand and available ship capacity

Liner container shipping company satisfies container shipping demand from both long-term contracts and spot market. Different from the shipping demand from long-term contracts whose freight rate is usually negotiated between the shipping company and the customer, the freight rate of the spot demand is usually determined by the shipping company itself. This paper thus focuses on how to determine the optimal freight rate of spot containers for each origin and destination (OD) pairs of a shipping network to maximize the total profit. To further reflect industry practice, two types of uncertainties are considered, i.e., the uncertain spot demand volume due to stochastic slot booking arrivals and cancelations, and the uncertain remaining ship capacity for the spot demand after satisfying other demand types with higher priority (e.g. delayed containers). This problem is first formulated as a two-stage stochastic nonlinear and nonconvex programming model. A tailored spatial branch-and-bound-and-Benders algorithm is then developed to obtain the global optimal solution of the model. Numerical experiments also demonstrate the efficiency of the solution algorithm and the applicability of the proposed model in improving the profit from the spot shipping demand.

The Constrained Air Transport Energy Paradigm in 2021

The increasing relevance of air transport as a contributor to climate change requires the development of emissions reduction technologies in a socio-economic and cultural context, where demand and air traffic have traditionally held sustained growth rates. However, the irruption of COVID-19 in 2020 has had an enormous negative impact on air travel demand and traffic volumes. Coincidentally, during 2020, new technology proposals for emissions reduction based on use of hydrogen and synthetic fuels have emerged from the aviation stake holders. By following a novel approach connecting the analysis of expectations of technology developments and their deployment into the fleet to market constraints, this study discusses how, even considering the new technology proposals and even if the COVID-19 has led to a completely different scenario in tourism and aviation, the air transport energy paradigm will remain unchanged in the upcoming decades as a consequence of market constraints, aircraft complexity, compliance with safety requirements, and extended life cycles. In this frame, aviation needs to keep on pursuing the abatement of its emissions while managing social expectations in a realistic manner and leaning on compensation schemes to achieve emissions contention while new technologies become serviceable in the longer term.

Profiling the implementation of rainwater harvesting in Bekasi, Indonesia

This research was raised based on water resource problems, which are currently becoming a global obstacle to overcome. Population growth impacted the demand for water resources, changed the hydrological cycle pattern in an area, and worsened with climate change, impacting season disaster. This research was conducted to see the profile of Bekasi City on rainwater harvesting so that the results of this study are expected to provide a big picture in the context of applying rainwater harvesting. Rainfall analysis uses dependable rainfall to cut down rainfall uncertainty and grant opportunities for a higher harvestable rainfall volume. Besides, a community approach was carried out to observe society’s water use patterns and their behavior towards rainwater harvesting. This study found that the volume of water demand in Bekasi varied in each District, which is 3.57-7.08 m3/person/month, and harvested rainwater can cover up 2.27%-12.73% of their needs during the wet season (December-April). The community has collected their rainwater at their homes by 49%. A comprehensive approach should have taken to attract people to harvest rainwater.

Percolation of heterogeneous flows uncovers the bottlenecks of infrastructure networks

Whether it be the passengers’ mobility demand in transportation systems, or the consumers’ energy demand in power grids, the primary purpose of many infrastructure networks is to best serve this flow demand. In reality, the volume of flow demand fluctuates unevenly across complex networks while simultaneously being hindered by some form of congestion or overload. Nevertheless, there is little known about how the heterogeneity of flow demand influences the network flow dynamics under congestion. To explore this, we introduce a percolation-based network analysis framework underpinned by flow heterogeneity. Thereby, we theoretically identify bottleneck links with guaranteed decisive impact on how flows are passed through the network. The effectiveness of the framework is demonstrated on large-scale real transportation networks, where mitigating the congestion on a small fraction of the links identified as bottlenecks results in a significant network improvement.

Attentional Engagement as Practice: A Study of the Attentional Infrastructure of Healthcare Chief Executive Officers

In this paper, we investigate the attentional engagement of chief executive officers (CEOs) of large healthcare organizations in England. We study attention ethnographically as something managers do—at different times, in context, and in relation to others. We find that CEOs match the challenges of volume, fragmentation, and variety of attentional demands with a bundle of practices to activate attention, regulate the quantity and quality of information, stay focused over time, and prioritize attention. We call this bundle of practices the CEO’s attentional infrastructure. The practices that compose the attentional infrastructure work together to ensure that CEOs balance paying too much with paying too little attention, sustain attention on multiple issues over time, and allocate attention to the issues that matter, while avoiding becoming swamped by too many other concerns. The attentional infrastructure and its component practices are constantly revised and adapted to match the changes in the environment and ensure that managers remain on top of the things that matter to them. The idea of a practice-based attentional infrastructure advances theory by expanding and articulating the concept of attentional engagement, a central element in the attention-based view of the firm. We also demonstrate the benefits of studying attention as practice, rather than as an exclusively mental phenomenon. Finally, we contribute to managerial practice by introducing a set of categories that managers can use to interrogate their existing attentional practices and address attentional traps and difficulties.

Estimating supply and demand elasticities of dissolving pulp, lignocellulose-based chemical derivatives and textile fibres in an emerging forest-based bioeconomy

In a growing bioeconomy, traditional forest products markets change and diversify. Fossil-based inputs in the chemical, textile, apparel and downstream industries can be replaced by lignocellulose-based products such as dissolving pulp, cellulose-based chemical derivatives and textile fibres. When looking ahead, these previous niche products are likely to gain in economic importance. So far, little attention has been paid to the characteristics of macroeconomic relations of emerging lignocellulose-based materials on macroeconomic level. Key economic parameters for such materials are not available neither at regional nor at global level. This work aims to contribute to a better understanding of the market behavior of emerging forest products that are not yet covered by forest products market analysis. Therefore, this paper investigates how lignocellulose-based products respond to changes of main economic drivers and compute global market elasticities for dissolving pulp, cellulose-based chemical derivatives and textile fibres. To conduct our evaluation, we first test historical input data for non-constancy in time series due to structural changes using change-point estimator (MOSUM test). We subsequently carry out a global econometric analysis of demand and supply elasticities with income (GDP) and real import and export prices as explanatory variables. By doing so, we deliver key information for the adaptation of forest-product market analysis and modelling to an upcoming bioeconomy. The results show several structural changes especially in price data between 1992 and 2015, thus supporting the use of time series cuts to divide the time line from 1992 to 2015 into three different sub-periods. Elasticities are subsequently estimated for each of the sub-periods. The results from this econometric analysis provide import demand and export supply elasticities of dissolving pulp, cellulose chemical derivatives and cellulose textile fibres. In addition, we present elasticity estimation for the apparent consumption of dissolving pulp. Our findings outline the significant relationship between both export supply and import demand volumes and relative changes in prices and income. Across time periods, elasticities of cellulose-based derivatives and textile fibres do not show a clear trend towards more elastic or inelastic coefficients. However, the price elasticities of dissolving pulp fluctuate strongly from inelastic to highly elastic over time. Elasticity estimates of export supply indicate that it is sensitive to international competitiveness which in turn is governed by international demand. Finally, we statistically show that the estimated price and income elasticities of import demand can be analogously interpreted as the demand elasticity of apparent consumption. This is of great importance for economic equilibrium models, such as GFPM or EFI-GTM, in order to simulate and analyze forest sector developments and scenarios.

Workforce training and operations planning for maintenance centres under demand uncertainty

Companies that provide repair & overhaul services to the users of complex technical systems are confronted with uncertain volume of demand when making tactical decisions such as workforce training and planning of repair operations over an annual planning horizon. Given the high importance of equipment availability (e.g. gas turbines) to the users (e.g, power plants), any delay in the delivery of repaired equipment caused by demand uncertainty would lead to significant penalties and loss of customer goodwill. In this paper, a two-stage stochastic programming model is proposed to obtain the optimal number of items to repair, spare part inventory, and the number of operators to train with the goal of minimising the total expected cost of maintenance operations and late delivery. Outsourcing and borrowing strategies are adopted as corrective measures to reduce the probability of late delivery in the emerge of demand uncertainty. Numerical findings illustrate the importance of integrating uncertainty into these operations planning decisions as well as the mitigation strategies in handling the cost of the system.

A Model of Queue Scalping

Recent years have witnessed the rise of queue scalping in congestion-prone service systems. A queue scalper has no material interest in the primary service but proactively enters the queue in hopes of selling his spot later. This paper develops a queueing-game-theoretic model of queue scalping and generates the following insights. First, we find that queues with either a very small or very large demand volume may be immune to scalping, whereas queues with a nonextreme demand volume may attract the most scalpers. Second, in the short run, when capacity is fixed, the presence of queue scalping often increases social welfare and can increase or reduce system throughput, but it tends to reduce consumer surplus. Third, in the long run, the presence of queue scalping motivates a welfare-maximizing service provider to adjust capacity using a “pull-to-center” rule, increasing (respectively, reducing) capacity if the original capacity level is low (respectively, high). When the service provider responds by expanding capacity, the presence of queue scalping can increase social welfare, system throughput, and even consumer surplus in the long run, reversing its short-run detrimental effect on customers. Despite these potential benefits, such capacity expansion does little to mitigate scalping and may only generate more scalpers in the queue. Finally, we compare and contrast queue scalping with other common mechanisms in practice—namely, (centralized) pay-for-priority, line sitting, and callbacks. This paper was accepted by Victor Martínez de Albéniz, operations management.

Exergy analysis of hydrogen-reduction based steel production with coal gasification-shaft furnace-electric furnace process

Carbon-free energy utilization in steel production is an effective way for China's iron and steel industry to achieve low carbon development. Thus, coal gasification-shaft furnace-electric furnace (CSE) technology, which use hydrogen-enriched gas for steel production, has recently become a sustainable topic of great concern. In the current study, the material flow analysis (MFA) and exergy assessment of the CSE process are conducted to investigate the material consumption and energy efficiency of this new steelmaking process. The exergy efficiency of the CSE process is calculated to be 50.11%, indicating a great potential for energy-saving. The results indicate that the coal gasification & gas purification that responsible for hydrogen-enriched gas production is the system with the largest exergy loss (account for 23.13% of the total exergy input), while the pelletizing system has the lowest efficiency (13.33%) due to heat loss. The key to further improve the thermal performance of this process lies in the heat recovery of the coal gasifier and pelletizing. It is also found that when the H2 content in reducing gas rise from 57.00% to 100.00%, the exergy efficiency of the shaft furnace is only increased by 1.58%, while the demand volume of reducing gas significantly increases from 1326.30 Nm3/t to 2201.50 Nm3/t. The environmental benefits of hydrogen reduction based steelmaking must be considered together with energy utilization and production cost. The present work should do helpful effort for the application and further improvement of the CSE process in China.

The Effect of Irrigation Rate on the Water Relations of Young Citrus Trees in High-Density Planting

The availability and proper irrigation scheduling of water are some of the most significant limitations on citrus production in Florida. The proper volume of citrus water demand is vital in evaluating sustainable irrigation approaches. The current study aims to determine the amount of irrigation required to grow citrus trees at higher planting densities without detrimental impacts on trees’ water relation parameters. The study was conducted between November 2017 and September 2020 on young sweet orange (Citrus sinensis) trees budded on the ‘US-897’ (Cleopatra mandarin x Flying Dragon trifoliate orange) citrus rootstock transplanted in sandy soil at the Southwest Florida Research and Education Center (SWFREC) demonstration grove, near Immokalee, Florida. The experiment contained six planting densities, including 447, 598, and 745 trees per ha replicated four times, and 512, 717, and 897 trees per ha replicated six times. Each density treatment was irrigated at 62% or 100% during the first 15 months between 2017 and 2019 or one of the four irrigation rates (26.5, 40.5, 53, or 81%) based on the calculated crop water supplied (ETc) during the last 17 months of 2019–2020. Tree water relations, including soil moisture, stem water potential, and water supplied, were collected periodically. In addition, soil salinity was determined. During the first year (2018), a higher irrigation rate (100% ETc) represented higher soil water contents; however, the soil water content for the lower irrigation rate (62% ETc) did not represent biological stress. One emitter per tree regardless of planting density supported stem water potential (Ψstem) values between −0.80 and −0.79 MPa for lower and full irrigation rates, respectively. However, when treatments were adjusted from April 2019 through September 2020, the results substantially changed. The higher irrigation rate (81% ETc) represented higher soil water contents during the remainder of the study, the lower irrigation rate (26.5% ETc) represents biological stress as a result of stem water potential (Ψstem) values between −1.05 and −0.91 MPa for lower and higher irrigation rates, respectively. Besides this, increasing the irrigation rate from 26.5% to 81%ETc decreased the soil salinity by 33%. Although increasing the planting density from 717 to 897 trees per hectare reduced the water supplied on average by 37% when one irrigation emitter was used to irrigate two trees instead of one, applying an 81% ETc irrigation rate in citrus is more efficient and could be managed in commercial groves.

Inventory Timing: How to Serve a Stochastic Season

Problem Definition. Firms that sell products over a limited selling season often have only imperfect information about (a) the exact timing of that season, (b) the demand volume to expect, and (c) the temporal distribution of demand over the selling season. Given these uncertainties, firms must determine not only how much inventory to stock but also when to make that inventory available to customers. We ask: What is a firm’s optimal inventory quantity and timing for products sold during a stochastic selling season? Academic and Practical Relevance. Managers are frequently confronted with challenging inventory timing decisions, especially when the products they manage exhibit high inventory holding costs and substantial uncertainty concerning the pattern of customer demand. Although the newsvendor literature has developed a thorough understanding of the firm’s optimal inventory quantity, it has failed to inform decision makers about choosing the optimal inventory timing. Methodology. We develop a theoretical model of a firm that sells a product over a stochastic selling season, and we study how this firm should choose its inventory timing and inventory quantity so as to maximize expected profits. Results. We derive the firm’s optimal inventory policy—which comprises inventory timing and inventory quantity—and discuss the interaction effects between these two decisions. We also identify the effects of optimal inventory timing on a firm’s ability to satisfy customer demand and show how early inventory timing can be detrimental to customer service. Managerial Implications. Our core insights imply two immediate recommendations for managers. First, optimal inventory timing is an effective weapon for combatting both high inventory holding costs and high levels of uncertainty in the firm’s customer demand pattern. Second, naive decision rules (e.g., “earlier is better”) may reduce not only the firm’s profits but also its capacity to serve customer demand.

Indoor precise point positioning with pseudolites using estimated time biases iPPP and iPPP-RTK

The global navigation satellite system (GNSS) provides outstanding positioning services for outdoor activities with sufficient accuracies, but it has poor indoor performance. Indeed, indoor positioning is also expected to achieve the outdoor positioning level to cater to an even higher volume of user demands. A pseudolite (PL), also called a pseudosatellite, is a ground-based positioning system that offers flexible deployment and accurate “orbits”. The PL system can carry on the role of the GNSS to provide precise positioning for indoor users. The clock differences originating from ground-based transmitters cause unsynchronized timing issues and impede attempts to fix the integer ambiguity. Numerous studies have been conducted with an emphasis on time synchronization to obtain this ambiguity-fixed solution by employing multiple transceivers in transmitter-receiver combinations for self-calibration inside a regional network of the ground-based system. However, this process requires a large investment and complicates the positioning owing to its intricate implementation. Actually, time synchronization can easily be achieved with a transmitter-only PL system at a low cost once the clock bias between transmitters is properly handled. Thus, we propose and present indoor precise point positioning (iPPP) and indoor PPP-real-time kinematic (iPPP-RTK) to handle the PL clock bias efficiently. Experiments demonstrate that the transmitter-only PL system can be time-synchronized without high cost or complicated operations and that centimeter level indoor precise positioning can be reliably achieved with our proposed methods.

Energy saving behavior in the marketing of startup projects and marketing activities of world high-tech enterprises

Methods. The results were obtained through the use of following methods: dialectical method of cognition, comparison and generalization – to clarify the concept of «energy-saving behavior of economic and social agents»; theories of marketing, logistics, competition and fuzzy logic and fuzzy plural numbers – when developing a methodological approach to the formation of product competitiveness aimed at respecting marketing energy-saving values; index approach – during the formation of the competitiveness index of high-tech enterprises; marketing, economic, graphic analysis – when calculating the sales volume of Siemens AG by regions of the world, establishing a variation in the maximum value of operating profitability in the areas of Siemens AG. Results. Components of energy-saving behavior of enterprises are defined, marketing activity and competitiveness of products of high-tech enterprise are investigated. The components of energy-saving behavior of enterprises are outlined in the interpretation of representatives of various scientific economic schools and organizations. It was found that the energy-saving behavior of economic and social agents reflects the integrated observance of the principles of the concept of sustainable development, aimed at safe interaction with the environment and the preservation of energy resources. The methodical approach of product competitiveness formation aimed at compliance with marketing energy-saving values on the principles of using fuzzy logic theory is proposed. It is determined that the competitiveness of enterprises is formed under the influence of such components as: the economic efficiency of the organization of e-logistics service, the success of marketing activities of fifth-level logistics virtual operators, the level of market concentration, the volume of demand and supply. The marketing activity of the international concern Siemens AG (Germany) was investigated, in particular its sales volume by regions of the world. It was established that the sale of high-tech products and services in the European region, including Germany, plays a significant role in the marketing activities of the concern. Novelty. The methodological approach of product competitiveness formation, aimed at compliance with marketing energy-saving values on the principles of using the fuzzy logic theory, consists in taking into account the components of competitiveness, mapping the functional directions of logistics, logistics service, forming density, continuity of logistics flows, energy saving, during comparison with logistic linguistic variables, which positively affects obtaining competitive advantages of high-tech enterprises. Practical value. It is proposed to achieve the economic effect of increasing the competitiveness of products of high-tech engineering enterprises based on the application of two supporting approaches: competitive and logistical.