Search Results (17)

Strategic bidding in day-ahead electricity markets requires generation companies to maximize expected profits while managing financial risks arising from market uncertainty and competitors’ strategic behavior. This paper proposes a game-theoretic risk-aware strategic bidding framework based on a Supply Function Nash Equilibrium (SFNE) for dominant market operators in a uniform-pricing day-ahead market. Each operator strategically determines cluster-level bidding markups for its heterogeneous generation portfolio while anticipating competitors’ strategies. Demand uncertainty is represented by a finite scenario set, and Conditional Value-at-Risk (CVaR) of profit shortfall is incorporated into each operator’s expected-profit objective. The resulting non-cooperative equilibrium is solved using a relaxed Nikaido–Isoda (NI) best-response algorithm with convergence criteria based on the relative NI gap, strategy variation, and utility variation. The framework is validated using publicly available Italian day-ahead market offer data, where technology-oriented clustering reduces the strategic decision dimension while preserving portfolio heterogeneity. The proposed algorithm satisfies all convergence criteria within approximately 54 iterations. Numerical results show that the proposed risk-aware SFNE reduces aggregate downside-profit risk by approximately 7% compared with the risk-neutral SFNE while maintaining comparable expected profitability and slightly lowering market-clearing prices and procurement costs. A realistic 24 h market simulation further confirms the robustness and applicability of the proposed framework under time-varying market conditions. Overall, the proposed framework provides an economically interpretable and computationally tractable benchmark for risk-aware strategic bidding in day-ahead electricity markets. Full article

The development of digital supply chains has significantly changed traditional supplier selection models that focus on static and cost-driven criteria. In addition to price, operational standards, service excellence, and contribution to the platform should be taken into account when evaluating sellers operating on dynamic, performance-oriented e-commerce platforms. This study addresses this gap by developing a comprehensive multi-criteria decision-making (MCDM) framework through a systematic literature review according to PRISMA methodology. Searches conducted in Web of Science, ScienceDirect, IEEE Xplore, Google Scholar, and Taylor & Francis yielded 4630 records from 2014 to 2025, of which 123 were analyzed using bibliometric mapping and thematic synthesis. The findings indicate a progressive diversification of evaluation criteria over time: while quality, delivery, and cost remain foundational, recent studies increasingly address customer service, search volume, and refined financial indicators such as profit and markup rate, pointing toward more multidimensional seller evaluation models. Through thematic synthesis of the indicators identified across the reviewed studies, we propose a four-dimensional framework encompassing financial sustainability, operational efficiency, quality and service standards, and market positioning. The study also discusses the implications of integrating artificial intelligence with multi-criteria and hybrid decision-making approaches for developing adaptive seller ranking systems. By synthesizing fragmented research, our framework offers strategic guidance for platform managers designing seller evaluation and allocation mechanisms. Full article

The objective of this study is to analyze the current situation of out-of-home catering (OHC) in Germany concerning the use of regional organic food using a case study; we also aim to determine the potential and challenges that exist in increasing the proportion of regional organic food in OHC. The food purchasing data from three canteens of the company were analyzed concerning regionality, seasonality, and organic share. The companies’ employees were asked about their willingness to pay and their attitude towards regional organic food using an online questionnaire. A price comparison between organically and conventionally grown food was carried out with food wholesalers’ product price lists. The study confirms the potential to increase the share of regional organic food in OHC. With their private purchasing behavior, eating habits and willingness to pay a surcharge for organic quality in the company restaurants, the consumers confirm that they support an increase in the regional organic share. Regional organic food could be purchased from (organic) wholesalers. However, the study also shows that the cost of sourcing organic food is on average 50% higher than that of conventional food and that this price markup is the main reason for consumers not buying organic food. Full article

It is currently essential to seek innovative solutions for sustainability and the efficient use of resources, rooted in bioeconomy principles and linked to the concepts of the circular economy. Technological innovations supporting the production of wood–plastic composites, using recycled materials, reduce the ecological footprint. The aim of the study was to present conclusions of the evaluation of the business plan concept’s effectiveness and to propose applications of traditional and innovative cost calculations resulting from the implementation of technological innovations in the production of wood–plastic composites in the forest-based sector in accordance with the principles of the circular economy. Using dynamic methods for evaluating business plan net present value, profitability index, internal rate of return, and discounted payback period, positive recommendations for project rentability were identified under both realistic and pessimistic scenarios. By applying traditional markup calculation, material cost savings of EUR 3.99/m³ were quantified, representing a relative saving of over 2% compared to traditional particle board. Verification of alternative machine hour rate calculation allows for more precise allocation of overhead costs into product pricing and provides the ability to respond swiftly to changes in input parameters. The findings have practical implications for the forest-based sector, as the use of recycled plastics can reduce production costs and increase the competitiveness of production. Full article

Price markups and firms’ Tobin’s Q ratios are widely believed to have been increasing in the past several decades. Various models for the calculation of price markups have been developed, each relying on the historically held definition of the ratio of price to marginal cost; however, all of these have methodological drawbacks, and some of the results they have produced have been poorly reflective of the near past wider macroeconomic experience. This paper defines a new approach for the definition and measurement of markup pricing, and it also avoids some of the issues surrounding the marginal cost approaches by using the measure of economic rent and the capital asset pricing model. The results show limited markup pricing for the UK’s FTSE 100 companies (2018–2023), but that certain real estate, technology/media and financial services/equity investment firms have enjoyed higher price markup levels. An analysis of the business models of these firms is used to qualitatively propose explanations for such markups. This work offers formal proof that that the expected price markup is equal to Tobin’s Q and finds that the empiric market level of markup is near equivalent to the market Tobin’s Q; the differences between the markup and Tobin’s Q at the level of the firm are equally assessed. This work challenges the general consensus that price markups are above one and have been increasing; it may also aid policy makers with respect to taxation policy and regulatory measures, as well as the financial management of firms in decisions concerning capital deployment and portfolio management. The method merits expansion to wider data sets, as well as to those from outside of the UK. Full article

This article analyzes the implicit hedging and liquidity costs of structured equity products offered by various financial institutions. We replicate several payoffs of structured products, compare the calculated fair values based on the Heston model as well as geometric Brownian motion, using various optimization techniques, and compare their fair values with the historic prices traded in the market. We find that implicit hedging costs range between 0.9% and 2.9% markup on the fair value, where we find the underlying market volatility to be the relevant driver of this range for complex structures, while market liquidity can be extracted as the only driver of markups for simple structures with no hedging requirements. Full article

While construction costs and housing prices are implicitly examined in the construction economics literature, dedicated studies on their theoretical underpinning are rare. In this study, we investigated the application of different pricing theories in Auckland by testing the relationship between house prices and construction costs in Auckland from 1995 to 2021. The results contrast the tendering pricing theory, which posits that construction prices are optimal mark-ups unaffected by market demand, with the full-cost pricing theory, which acknowledges the market-dependent nature of pricing. By using the Toda-Yamamoto’s granger-causality test and Pesaran’s Autoregressive Distributive Lag (ARDL) bound tests, we analysed the relationship between the house price index (HPI) and construction cost index (CCI). The result suggests a significant relationship between housing prices and construction costs in both the short and long term, supporting the predominance of the full-cost pricing theory in Auckland’s housing market. The finding highlights the potential need for property industry participants to evaluate the market structure of the construction industry, fostering a more competitive environment and paving the way for more effective supply-related housing policies. Full article

Utility model patent quality is vital for emerging countries to cultivate a strong domestic market and increase openness. Given China’s high-quality development, this study incorporates enterprise utility model patent quality and export domestic value-added rate (DVAR) into a unified analysis framework to explore their relationship using authorized patent data and financial and customs data of Chinese industrial enterprises from 2002 to 2014. The utility model patent data used to support this study’s findings were provided by the Incopat Patent Database, while the enterprise financial data and customs data were supplied by the RESSET Database. The empirical results show that: (i) utility model patent quality significantly contributes to enterprises’ export DVAR; (ii) factor-intensive heterogeneous analysis indicates that the utility model patent quality of capital-intensive enterprises has a more significant promotion effect on DVAR; (iii) the price–cost markup and the relative price of intermediate goods are crucial domestic channels for utility model patent quality to promote DVAR; and (iv) market segmentation moderates the mediating role of the domestic intermediate relative price. Therefore, the government should further improve the utility model system, focus on increasing domestic market advantages, and develop industry-specific patent guidance policies. This study contributes to the literature by exploring the influence of utility model patent quality on enterprises’ DVAR using an optimized utility model quality index, providing policy references for optimizing China’s utility model patent system and upgrading the import gains of enterprises. However, this study has some limitations, and future research should strengthen the subdivision of utility model patents in different industries and explore the economic performance of the combination of inventions and utility models. Full article

The bidding price is one of the important factors for construction enterprises in winning a bid. In the context of public bidding in the construction industry, in the process of group competition, how to estimate the individual bids to calculate their maximum value and the best price to improve the winning probability has become an important issue. In this research, based on the real option theory, the concept of group bidding environment is introduced to establish a real option price decision-making model for construction projects. The function of the model covers two external competitive environments: independent and coupled. Finally, through model inspection and parameter sensitivity analysis, the model is discussed in depth, and suggestions for model application are obtained. The research results show that the rule of the model results has optimization characteristics, and the numerical solution is consistent with the analytical solution, which has a certain price guidance role. In the independent bidding environment, their optimal bidding price is inversely proportional to the volatility level and the option period, and it is directly proportional to the estimated costs but has no obvious relationship with the number of competitors. Moreover, the average sensitivity of the optimal bidding price to the estimated costs, the volatility level and the option period are 35.06%, 9.77% and 7.70%, respectively; the optimal mark-up ratio is 1.078. In the coupled bidding environment, the concentration of competitors’ prices and the optimal price will increase significantly, by about 2.37%, and the corresponding winning probability and weighted option value will increase by about 9.36% and 28.03%, respectively. The research results can provide price optimization for bidding activities with real option characteristics and improve the price winning rate, but the selection of price mode and parameter setting need to be set by enterprises according to industry characteristics and actual conditions. Full article

Globalized in 1995 through the TRIPs Agreement, humanity’s dominant mechanism for encouraging innovations involves 20-year product patents, whose monopoly features enable innovators to reap large markups or licensing fees from early users. Exclusive reliance on this reward mechanism in the pharmaceutical sector is morally problematic for two main reasons. First, it imposes a great burden on poor people who cannot afford to buy patented treatments at monopoly prices and whose specific health problems are therefore neglected by pharmacological research. Second, it discourages pharmaceutical firms from fighting diseases at the population level with the aim of slashing their incidence. These problems can be alleviated by establishing a supplementary alternative reward mechanism that would enable pharmaceutical innovators to exchange their monopoly privileges on a patented product for impact rewards based on the actual health gains achieved with this product. As such, an international Health Impact Fund (HIF) would create powerful new incentives to rapidly develop remedies against diseases concentrated among the poor, provide such remedies with ample care at very low prices, and deploy them strategically to contain, suppress, and ideally eradicate the target disease. By promoting innovations and their diffusion together, the HIF would greatly enlarge the benefits, and thereby also the cost-effectiveness, of the pharmaceutical sector, especially in favor of the world’s poor. Full article

Prices respond to equate supply and demand. However, price-setting in low-volume or “thin” markets is a challenge as is determining which items to carry. We present an algorithm that takes into account a store’s fixed costs, the cost of goods sold, prices, and listing duration to determine the portfolio of items to maximize profits. Prices can then be assigned as a mark-up over cost. The usefulness of this approach is demonstrated by applying it to a store on eBay in which the seller needs to meet a profit threshold. The findings identify how sellers of unusual items can effectively determine which items to list and how to set price to reach profit goals. Full article

In a competitive electricity market, generation capacities can exactly cover their full costs. However, the real market deviates from this ideal in some aspects. One is the concern of non-existent or insufficient scarcity prices. We present an iterative method in a linear optimization model to investigate the profitability of assets in the absence of scarcity prices and how the system changes when this risk is incorporated into investors’ expectations. Therefore, we use a two-step optimization of capacity planning and unit commitment. Iteratively, mark-ups at the height of uncovered costs are added to investment costs. This typically leads to a system with better investment profitability while keeping the system cost increase low. The methodology is applied to a simplified brownfield generation system, targeting CO₂-free power generation within 25 years. In a model with annual foresight of actors, iterations result in a generation system with significantly lower (or even no) uncovered costs for new investments within ten or fewer iterations. Our example case with full foresight shows that early-added gas (combined cycle) and wind onshore capacities are able to recover their full costs over a lifetime, even without scarcity prices. However, the contribution margin gap remains high, especially for storage and biomass. Full article

At present, the purchasing prices for silicon-based photovoltaic modules with 20% efficiency and more are between 20 and 40 EURct/W_p. These numbers correspond to 40 to 80 EUR/m² and are in the same range as the mounting costs (material prices plus salaries) of such modules. Installers and operators of photovoltaic systems carefully balance the module and mounting costs when deciding among modules of different efficiencies. This contribution emulates the installer’s decision via a simple, analytical module mounting decision (Mo²De) model. A priori, the model, and the resulting conclusions are completely independent of the photovoltaically active material inside the modules. De facto, however, based on the present state (cost, efficiency, reliability, bankability, etc.) of modules fabricated from (single) crystalline Si cells, conclusions on other photovoltaic materials might also be drawn: On the one hand, the model suggests that lower-efficiency modules with efficiencies below 20% will be driven out of the market. Keeping in mind their installation costs, installers will ask for large discounts for lower-efficiency modules. Technologies based on organic semiconductors, CdTe, CIGS, and even multicrystalline Si, might not survive in the utility market, or in industrial and residential applications. Moreover, this 20% mark will soon reach 23%, and finally will stop at around 25% for the very best, large-area (square meter sized) commercial modules based on single crystalline silicon only. On the other hand, it also seems difficult for future higher-efficiency modules based on tandem/triple cells to compete with standard Si-based reference modules. Compared to their expected higher efficiency, the production costs of tandem/triple cell modules and, therefore, also their required markup in sales, might be too high. Depending on the mounting cost, the Mo²De-model predicts acceptable markup values of 1 EURct/W_p (for low mounting costs of around 10 EUR/m²) to 11 EURct/W_p (for high mounting costs of 100 EUR/m²) if the module efficiency increases from 23% to 30%. Therefore, a 23% to 24% module efficiency, which is possible with silicon cells alone, might be enough for many terrestrial photovoltaic applications. Full article

On the border of two phases of a building life cycle (LC), the programming phase (conception and design) and the execution phase, a contractor is selected. A particularly appropriate method of selecting a contractor for the construction market is the tendering system. It is usually based on quality and price criteria. The latter may involve the price (namely, direct costs connected with works realization as well as mark-ups, mainly overhead costs and profit) or cost (based on the life cycle costing (LCC) method of cost efficiency). A contractor’s decision to participate in a tender and to calculate a tender requires an investment of time and company resources. As this decision is often made in a limited time frame and based on the experience and subjective judgement of the contractor, a number of models have been proposed in the literature to support this process. The present paper proposes the use of statistical classification methods. The response obtained from the classification model is a recommendation to participate or not. A database consisting of historical data was used for the analyses. Two models were proposed: the LOG model—using logit regression and the LDA model—using linear discriminant analysis, which obtain better results. In the construction of the LDA model, the equation of the discriminant function was sought by indicating the statistically significant variables. For this purpose, the backward stepwise method was applied, where initially all input variables were introduced, namely, 15 identified bidding factors, and then in subsequent steps, the least statistically significant variables were removed. Finally, six variables (factors) were identified that significantly discriminate between groups: type of works, contractual conditions, project value, need for work, possible participation of subcontractors, and the degree of difficulty of the works. The model proposed in this paper using a discriminant analysis with six input variables achieved good performance. The results obtained prove that it can be used in practice. It should be emphasized, however, that mathematical models cannot replace the decision-maker’s thought process, but they can increase the effectiveness of the bidding decision. Full article

Frequent price discounts have become one of the features of retail chains in the Czech Republic. Discounts are most often provided for products popular with customers. One of the products that is subject to frequent discounts is milk. Several expert opinions estimate that up to 50% of milk is sold with frequent price discounts. Price pressure on farmers and food producers owing to frequent price promotions is supported by the purchasing power of retailers and, in extreme cases, leads to sub-cost purchasing prices. These facts set up the framework to assess the impact of frequent price discounts on policymaking, including tax administration. One of the effects of selling goods at discounts is lower VAT collection from shops, and thus lower revenue to the state budget. This paper attempts to estimate one of the potential impacts of frequent price discounts, namely the loss of VAT for the state budget due to low retail prices of milk. Theoretical estimation of the effect of frequent price discounts on VAT can help to assess policy that touches on mark-ups in specific markets, such as food. The estimation is based on data obtained from Czech Statistical Office, FADN, and Orbis databases and employs Monte Carlo simulation to capture the stochastic element of retail markups. Sub-cost prices of producers of milk have a more significant negative effect on VAT revenue than prices of other supply chain participants. The theoretical effect on VAT revenue is estimated to be in the range from a negative effect of 14.9 billion CZK to a positive effect of 7.4 billion CZK. Values of zero VAT effect points (mark-ups of producers, dairies, and retailers) are shown, as well as the critical value of price elasticity of demand (−0.1715), at which the effect of frequent price discounts on VAT revenue is zero. Full article