Extra Profit Research Articles

An alternative to methanol recovery from ternary mixture: Replacing extractive with reactive distillation for maximizing economical potential and resource recovery

This paper investigates the recovery of methanol from the propylene oxide (PO)/methanol/water mixture using reactive distillation (RD). The mixture presents a challenge due to the azeotrope formation between PO and methanol. To overcome this challenge, three RD scenarios, designated as Case 1, Case 2, and Case 3, are proposed. The primary principle underlying these cases is leveraging a reaction between PO and water, resulting in the production of propylene glycol (PG). This reaction consumes PO and thus eliminates the PO-methanol azeotrope, and reduces reboiler duty via the release of reaction heat. Case 1 utilizes one reactive distillation column (RDC) and one conventional distillation column (CDC) to recover methanol while reducing a quarter of the water content via the PO-water reaction. High purity methanol is obtained in the RDC distillate, while high purity PG is collected at the bottom of the CDC. Likewise, Case 2 follows the same approach as Case 1, with an additional PO stream to halve the water content. On the other hand, Case 3 employs a single RDC with a greater additional PO stream to react with all water content in the mixture, yielding high purity methanol at the distillate and PG at the bottom. These cases are simulated using Aspen Plus software, and their designs are optimized to minimize the total annual cost (TAC). The results are compared to a base case, represented by the side-stream extractive distillation (SSED) method. Cases 1, 2, and 3 demonstrate TAC reductions of 7.8 %, 27.7 %, and 60 %, respectively, compared to the base case. Additionally, the PG produced by the PO-water reaction presents opportunities for generating extra profit of 6.356 × 107 $ a−1, 7.248 × 107 $ a−1, and 8.98 × 107 $ a−1 in Cases 1, 2, and 3, respectively. Given the financial benefits observed in each case, these configurations may serve as attractive alternative methods for methanol recovery from the PO/methanol/water mixture.

Distortionary effects of PPP loans on business competition

We study the effects of PPP loans on business competition. We start by introducing temporary cash subsidies into a model of monopolistic competition with differentiated products and heterogeneous production costs. We test the predictions of our model in a sample of U.S. airport hotels for which we observe daily demand, prices, output, and profits. Consistent with model predictions, less profitable businesses were more likely to apply for PPP loans. Businesses with active PPP loans reduced prices, boosting output and profits relative to non-PPP competitors. Those relative differences were reversed once PPP loans expired. We calculate that, for every dollar of PPP subsidies, PPP hotels earned 72.4 cents in extra profits and non-PPP competitors lost 71.4 cents in aggregate. Our results suggest that the PPP initiative distorted competition, imposing significant costs on businesses that chose to forgo these loans.

Reputation management in turmoil—An analysis of the clashing narratives in the introduction of a “salmon tax” in Norway

AbstractThis study deals with reputation management, addressing collective issues, strategic communication by the government, and the dynamics between this communication and counter‐symbols from societal stakeholders. Empirically, it examines the political debates in Norway in recent years regarding the conflict over establishing a “ground rent” tax on extra profit earned through use of natural resources belonging to the community, related to salmon farming. The overall research question is how major concepts from reputation theory can explain the process and outcome of the decision‐making process. A main finding is that reputation varies across reputational dimensions and actors, and between government and audiences. Another is that it is necessary to examine reputation in relation to the field, the actors, and the task environment it concerns. The study also shows that reputation management is informed by the politics of reputation, revealing the challenge of balancing evidence‐based policy making and being responsive to opinion‐based stakeholder input, and that reputational threats and strategic communication are interlinked.

Repositioning to sink: The pricing and quality decisions for product line considering the sinking market

Opening up new markets (e.g., the sinking market) is one way to boost growth momentum, especially with the decrease in the rate of technological development and the impact of the black swan event (e.g., the COVID-19 pandemic). Considering the difficulty and cost of developing new products, repositioning existing products by a price markdown is an easier way to expand the market. Companies can implement different pricing strategies for different products to target different markets and make extra profits, but products entering the sinking market may deeply erode the original market. Therefore, balancing the advantages and disadvantages of entering the sinking market is a significant challenge for firms selling products as a product line. By building a theoretical model, we investigate the optimal product line repositioning strategy when companies decide to expand the market. First, we examine the optimal conditions for companies to enter a sinking market. We then analyze the optimal product line strategy in the sinking market. Furthermore, we investigate the interaction between repositioning strategy and quality decisions. The main results indicate that with the increase of the consumers’ willingness to pay at the sinking market and the decrease of the production cost, the seller's motivation to enter the sinking market would be greater. More importantly, entering the sinking market with higher quality can also be the optimal decision. What's more, we also find that the seller implementing low-quality repositioning strategy may prefer fiercer product erosion. Interestingly, the consideration of the quality decision would motivate the seller to enter the sinking market more aggressively even when the production cost is relatively high. Yet, this motivation would be weakened when the production cost is relatively low.

Coupling and Quantifying Sustainability and Resilience in Intelligent Buildings

Over recent years, the sustainability and resilience concept has increased its significance in the construction industry. Sustainability is associated with implementing best practices in the construction industry, while resilience is the adaptability and tolerance of systems in harsh conditions. The concepts are learned in the construction process. Moreover, building automation is growing rapidly, and buildings are becoming increasingly dependent on complex systems and technology and susceptible to unanticipated failure. Though sustainability and resilience concepts are interlinked, limited research quantifies their combination, resulting in a limited comprehension of how both concepts interact during application by developers in a smart building. Therefore, this study has established a financial model that employs Net Present Value (NPV) in studying the inference and clampdown of investment in both concepts. NPV was estimated using indirect and direct costs and benefits derived from the continuous integration of sustainability and resilience in a smart building. To quantify sustainability, its three components had to be quantified. Reduced energy expenditure and government environmental incentives were used to calculate the environmental component. Workers’ cost savings, fire insurance cost savings, and additional system maintenance costs were used to calculate the economic component. The social component of sustainability measured hard-to-quantify attributes like productivity, indoor environment quality, reputation, extra profit, services, and safety. To quantify them, a survey and RII method were used. The two concepts were then coupled by estimating the benefits and costs of installing and keeping resilience tools in design that are sustainable in the smart building and the impact study on the NPV outcome. Application of the design model was also carried out on four smart buildings that were selected in Dubai. The result indicated that coupling sustainable approaches and resilience yields higher NPV by at least 22%. Nevertheless, for NPV to be maintained positively and reduce the cost of failure, faulty detection tools should be assimilated while designing sustainable and smart buildings. The findings of this study will contribute to the benefit of other researchers, developers, investors, managers, engineers, and anyone who is involved in the design or construction process of intelligent buildings.

Critical Review on Metal‐Based Cosmetic Products

AbstractMost people utilize cosmetics to enhance or improve their physical appearance, regardless of their gender, race, or age. Heavy metals (HMs) are impurities or ingredients in many cosmetic products. According to recent studies, these metals can result in a variety of skin and health issues. Numerous studies demonstrate that the mismanaged formulation of such products without sufficient standardization of toxic metals throughout the production process is the primary reason for the high level of HM contamination in the samples. In order to prevent human exposure to such dangerous HMs, it is vital to monitor and manage the fate of HMs in cosmetic items, especially unbranded ones. Due to the wasteful interest of producers in making extra profit, the standards are not being imposed. Moreover, consumers are also ready to compromise with the product due to their unawareness of its hazardous impact on their skin and bodies. Short‐term results on their looks may cause fatal effects on their health. Another significant issue that requires attention is the lack of safety regulations in the country for evaluating HMs in cosmetic products. Additionally, there is an urgent need to establish acceptable limits for potential impurities in cosmetic products that must be enforced at local levels. This review provides a comprehensive insight into the content of HMs in cosmetics and their effects on several organs and the site of application.

Pricing and coordination in a dual-channel supply chain considering internet celebrity’s sales effort and personal influence

The main purpose of this paper is to study the coordination, price and sales effort decisions of a dual channel supply chain under live streaming commerce mode. In nowadays’ e-commerce age, more and more people have interest in live streaming especially after the outbreak of COVID-19, but the research on live streaming supply chain is lacking. To fill this gap, a supply chain composed of a manufacturer and an internet celebrity is established, in which the demand is affected by the internet celebrity’s sales effort and personal influence. Considering different power structures of the supply chain, price and sales effort decisions are studied in four models: Nash, manufacturer dominant (MD), internet celebrity dominant (KD) and cooperative game models. Subsequently, the feasible region of bargaining game is discussed in terms to share the extra profits and coordinate the supply chain. The manufacturer and the internet celebrity can be coordinated through bargaining problem in the cooperation model, and the extra profits sharing ratio is depend on each other’s bargaining power. Numerical analysis is further provided to test the propositions and show the impacts of market share rate, internet celebrity’s commission rate and personal influence on supply chain’s performance.

Windfall Profit Taxation in Europe (and Beyond)

In 2022, the European Commission introduced, for the first time in its history, a windfall profit tax to be applied on “excessive” profits realized by qualified businesses operating in the “Oil and Gas” sector. Immediately after its implementation, questions arose as to its sustainability and its consistency with constitutional principles of the different member states regulating the domestic power to tax. To assess the consistency with the aforesaid rules, the article samples two countries, inside and outside the EU (Italy and Australia, respectively), and the historical precedents of the matter. Italy has been chosen due to the particularly stringent set of principles regulating the power of the legislature to tax, and Australia has been chosen because of the long-standing experience with superprofit taxes. In most of the scenarios analyzed, one common feature emerged: the complexity in defining the “Extra” nature of the profits and, consequently, the uncertainties in the calculation of the taxable base. In the case of Italy, for instance, the legislator had to intervene in several different moments to fine-tune the taxable base and restore certainty to the tax system. As a conclusion, while the taxation of extra profits should not per se be disregarded, its implementation demands a more robust and precise legal framework together with the understanding that the introduction of such a levy would be a one-way journey for the tax systems: windfall profits taxes would be here to stay.

Insights on the Theory of Robust Games

AbstractA robust game is a distribution-free model to handle ambiguity generated by a bounded set of possible realizations of the values of players’ payoff functions. The players are worst-case optimizers and a solution, called robust-optimization equilibrium, is guaranteed by standard regularity conditions. The paper investigates the sensitivity to the level of uncertainty of this equilibrium focusing on robust games with no private information. Specifically, we prove that a robust-optimization equilibrium is an $$\epsilon $$ ϵ -Nash equilibrium of the nominal counterpart game, where $$\epsilon $$ ϵ measures the extra profit that a player would obtain by reducing his level of uncertainty. Moreover, given an $$\epsilon $$ ϵ -Nash equilibrium of a nominal game, we prove that it is always possible to introduce uncertainty such that the $$\epsilon $$ ϵ -Nash equilibrium is a robust-optimization equilibrium. These theoretical insights increase our understanding on how uncertainty impacts on the solutions of a robust game. Solutions that can be extremely sensitive to the level of uncertainty as the worst-case approach introduces non-linearity in the payoff functions. An example shows that a robust Cournot duopoly model can admit multiple and asymmetric robust-optimization equilibria despite only a symmetric Nash equilibrium exists for the nominal counterpart game.

Comparative Chemical Profiling and Antimicrobial/Anticancer Evaluation of Extracts from Farmed versus Wild Agelas oroides and Sarcotragus foetidus Sponges.

Marine sponges are highly efficient in removing organic pollutants and their cultivation, adjacent to fish farms, is increasingly considered as a strategy for improving seawater quality. Moreover, these invertebrates produce a plethora of bioactive metabolites, which could translate into an extra profit for the aquaculture sector. Here, we investigated the chemical profile and bioactivity of two Mediterranean species (i.e., Agelas oroides and Sarcotragus foetidus) and we assessed whether cultivated sponges differed substantially from their wild counterparts. Metabolomic analysis of crude sponge extracts revealed species-specific chemical patterns, with A. oroides and S. foetidus dominated by alkaloids and lipids, respectively. More importantly, farmed and wild explants of each species demonstrated similar chemical fingerprints, with the majority of the metabolites showing modest differences on a sponge mass-normalized basis. Furthermore, farmed sponge extracts presented similar or slightly lower antibacterial activity against methicillin-resistant Staphylococcus aureus, compared to the extracts resulting from wild sponges. Anticancer assays against human colorectal carcinoma cells (HCT-116) revealed marginally active extracts from both wild and farmed S. foetidus populations. Our study highlights that, besides mitigating organic pollution in fish aquaculture, sponge farming can serve as a valuable resource of biomolecules, with promising potential in pharmaceutical and biomedical applications.

The Predictability of Stock Price: Empirical Study on Tick Data in Chinese Stock Market

Whether or not stocks are predictable has been a topic of concern for decades. The efficient market hypothesis (EMH) says that it is difficult for investors to make extra profits by predicting stock prices, but this may not be true, especially for the Chinese stock market. Therefore, we explore the predictability of the Chinese stock market based on tick data, a widely studied high-frequency data. We obtain the predictability of 3, 834 Chinese stocks by adopting the concept of true entropy, which is calculated by Limpel-Ziv data compression method. The Markov chain model and the diffusion kernel model are used to compare the upper bounds on predictability, and it is concluded that there is still a significant performance gap between the forecasting models used and the theoretical upper bounds. Our work shows that more than 73% of stocks have prediction accuracy greater than 70% and RMSE less than 2 CNY under different quantification intervals with different models. We further take Spearman's correlation to reveal that the average stock price and price volatility may have a negative impact on prediction accuracy, which may be helpful for stock investors.

Possible Alternatives: Identifying and Quantifying Adulteration in Buffalo, Goat, and Camel Milk Using Mid-Infrared Spectroscopy Combined with Modern Statistical Machine Learning Methods.

Adulteration of higher priced milks with cheaper ones to obtain extra profit can adversely affect consumer health and the market. In this study, pure buffalo milk (BM), goat milk (GM), camel milk (CM), and their mixtures with 5-50% (vol/vol) cow milk or water were used. Mid-infrared spectroscopy (MIRS) combined with modern statistical machine learning was used for the discrimination and quantification of cow milk or water adulteration in BM, GM, and CM. Compared to partial least squares (PLS), modern statistical machine learning-especially support vector machines (SVM), projection pursuit regression (PPR), and Bayesian regularized neural networks (BRNN)-exhibited superior performance for the detection of adulteration. The best prediction models for the different predictive traits are as follows: The binary classification models developed by SVM resulted in differentiation of CM-cow milk, and GM/CM-water mixtures. PLS resulted in differentiation of BM/GM-cow milk and BM-water mixtures. All of the above models have 100% classification accuracy. SVM was used to develop multi-classification models for identifying the high and low proportions of cow milk in BM, GM, and CM, as well as the high and low proportions of water adulteration in BM and GM, with correct classification rates of 94%, 100%, 100%, 99%, and 100%, respectively. In addition, a PLS-based model was developed for identifying the high and low proportions of water adulteration in CM, with correct classification rates of 100%. A regression model for quantifying cow milk in BM was developed using PCA + BRNN, with RMSEV = 5.42%, and RV2 = 0.88. A regression model for quantifying water adulteration in BM was developed using PCA + PPR, with RMSEV = 1.70%, and RV2 = 0.99. Modern statistical machine learning improved the accuracy of MIRS in predicting BM, GM, and CM adulteration more effectively than PLS.

Repurchase or pledge? Financing and production decisions of engineering machinery remanufacturing firms

Under carbon cap and trade policy, engineering machinery firms have engaged in remanufacturing and invested in carbon emission reduction technologies. However, they often struggle with a lack of funding, but carbon quota financing offers a solution. Taking a capital-constrained engineering machinery remanufacturer as the research object, this paper first formulates four decision models, i.e. (no capital constraints, no financing), (capital constraints, no financing), (capital constraints, carbon quota repurchase financing) and (capital constraints, carbon quota pledge financing), then the equilibrium results are compared. Finally, the numerical simulations are performed to study the impact of carbon emission reduction and quality uncertainty of recycled products. The results show that if remanufacturers possess adequate carbon quotas, carbon quota pledge financing can always improve profits effectively, otherwise, the effectiveness of financing strategies depends on the difference between extra profits and financing costs. Both financing strategies can increase the output of new products and reduce that of remanufactured products. Increasing the quality threshold of recycled products is beneficial for remanufacturing, environmental protection and profits. Investing in carbon emission reduction benefits remanufacturing and the environment, however, it reduces remanufacturers' profits in the short term.

Don’t go on holiday in August! Market reaction to an unexpected windfall tax on banks

Using an event study approach, this paper investigates the stock market reaction to the unexpected announcement of a windfall tax on banks’ extra profits. We show that investors negatively perceive the introduction of the tax, with more pronounced reactions for banks expected to be more highly burdened. This evidence is corroborated when we investigate the cross-sectional determinants of banks’ returns and cumulative abnormal returns. Overall, the results suggest that investors negatively price excess profits taxes and contribute to our understanding of how stock markets respond to tax policy changes.

ESMAC: Efficient and Secure Multi-Owner Access Control With TEE in Multi-Level Data Processing

Traditional data access control schemes only prevent unauthorized access to private data with a single owner. They are not suitable for application in a Multi-Level Data Processing (MLDP) scenario, where data are processed by a series of parties who also insert new data. Hence, the accumulated dataset should be protected through access control handled by hierarchically-structured parties who are at least partial data owners in MLDP. Existing multi-owner access control schemes mainly focus on controlling access to co-owned data of multiple entities with the equal ownership, but seldom investigates how to apply access control in MLDP. In this paper, we base the off-the-shelf Trusted Execution Environment (TEE), Intel SGX, to propose an Efficient and Secure Multi-owner Access Control scheme (ESMAC) for access authorization in MLDP. Moreover, to prevent unauthorized data disclosure by non-root data owners aiming to gain extra profits, we further introduce undercover polices to supervise their behaviors. Specifically, we design a data protection scheme based on game theory to decide the payoffs and punishments of honest and dishonest data owners, which motivates data owners to behave honestly when claiming ownership over data. Through comprehensive security analysis and performance evaluation, we demonstrate ESMAC's security and effectiveness.

Freshness-Keeping Strategy of Logistics Service Providers: The Role of the Interaction between Blockchain and Overconfidence

As a result of the increasing scrutiny of fresh products, greengrocers are now forced to concern themselves with the deterioration of their products’ freshness and employ blockchain technology as a tracing system. However, in the logistics system, the third-party logistics service provider (LSP) is motivated to be overconfident in order to extract extra profits, thus intensifying the dilemma faced by the fresh agricultural product industry. This paper focuses on the association between blockchain technology and overconfidence, in which the third-party LSP is supposed to overestimate the effect of the retailer’s freshness keeping measures. Differing from the previous literature, we analyze a situation wherein blockchain technology is adopted with explicit execution. Based on the optimal control model, we obtained three main conclusions: First, the overconfidence of a third-party LSP does not damage the logistics system but changes the freshness-keeping strategy of the retailer. Second, interestingly, although blockchain technology performs effectively when it is adopted as an initially established system with a freshness keeping strategy, it is not always a wise decision for managers to adopt a blockchain, especially when adopting it as a countermeasure for overconfidence. Third, we found that blockchain technology has a greater effect on freshness-keeping than overconfidence. Thus, in the fresh agricultural product industry, managers should adopt blockchain technology before overconfidence occurs and pay more attention to exogenous prices and freight to decide whether to adopt blockchain technology.

Making opportunity sales in attended home delivery

Research on time window management in attended home delivery mainly focuses on influencing customers’ delivery time choices to reduce monetary and environmental costs. In this study, we adopt a different perspective and propose exploiting otherwise idle time and vehicle capacities to generate extra profits through opportunity sales for e-groceries. We consider nudging potential target customers (residing in locations that are ”easy” to insert into the delivery tours) with push notifications to generate new sales. These customers are incentivized for purchases by dropping the terms imposed on standard e-grocery sales such as service fees or minimum purchase quantities. Managing the delivery operations for this innovative business model requires concurrently choosing the target customers and planning the vehicle routes under the offer acceptance and response time uncertainties. To solve this challenging problem, we propose an integer linear programming model that enables a decomposition of the problem into a routing problem and several customer selection problems. For the solution to the customer selection problems, we propose mathematical models with varying risk-taking levels. We also investigate the benefits of dynamic policies to take advantage of the information revealed during the delivery operations in order to adjust customer selection and vehicle routing decisions. Our extensive numerical experiments show that these models, equipped with dynamic decision making, can compete with the risk-ignorant models for the total profit while generating more sales per offer, as well as ensuring timely execution of the delivery operations.

Genetic dissection of 26 meat cut, meat quality and carcass traits in four pig populations

BackgroundCurrently, meat cut traits are integrated in pig breeding objectives to gain extra profit. However, little is known about the heritability of meat cut proportions (MCP) and their correlations with other traits. The aims of this study were to assess the heritability and genetic correlation of MCP with carcass and meat quality traits using single nucleotide polymorphism chips and conduct a genome-wide association study (GWAS) to identify candidate genes for MCP.ResultsSeventeen MCP, 12 carcass, and seven meat quality traits were measured in 2012 pigs from four populations (Landrace; Yorkshire; Landrace and Yorkshire hybrid pigs; Duroc, and Landrace and Yorkshire hybrid pigs). Estimates of the heritability for MCP ranged from 0.10 to 0.55, with most estimates being moderate to high and highly consistent across populations. In the combined population, the heritability estimates for the proportions of scapula bone, loin, back fat, leg bones, and boneless picnic shoulder were 0.44 ± 0.04, 0.36 ± 0.04, 0.44 ± 0.04, 0.38 ± 0.04, and 0.39 ± 0.04, respectively. Proportion of middle cuts was genetically significantly positively correlated with intramuscular fat content and backfat depth. Proportion of ribs was genetically positively correlated with carcass oblique length and straight length (0.35 ± 0.08 to 0.45 ± 0.07) and negatively correlated with backfat depth (− 0.26 ± 0.10 to − 0.45 ± 0.10). However, weak or nonsignificant genetic correlations were observed between most MCP, indicating their independence. Twenty-eight quantitative trait loci (QTL) for MCP were detected by GWAS, and 24 new candidate genes related to MCP were identified, which are involved with growth, height, and skeletal development. Most importantly, we found that the development of the bones in different parts of the body may be regulated by different genes, among which HMGA1 may be the strongest candidate gene affecting forelimb bone development. Moreover, as previously shown, VRTN is a causal gene affecting vertebra number, and BMP2 may be the strongest candidate gene affecting hindlimb bone development.ConclusionsOur results indicate that breeding programs for MCP have the potential to enhance carcass composition by increasing the proportion of expensive cuts and decreasing the proportion of inexpensive cuts. Since MCP are post-slaughter traits, the QTL and candidate genes related to these traits can be used for marker-assisted and genomic selection.

Climate Change and Economic Theory -- A Neo-Ricardian Approach to the Economy of Climate Protection

The Stern Review (2007) is the most comprehensive work to date on anthropogenic climate change from an economic perspective. It caused a general uproar because for the first time a renowned economist recommended the rapid implementation of expensive measures against climate change because hesitation would be even more expensive in the future. Nonetheless, the Stern Review moves in the familiar orbit of neoclassical theory, which supplanted classical theory (Smith, Ricardo, Marx) towards the end of the 19th century and is still dominant in academia today. Neoclassicism has made many contributions to environmental economics, but it seems to fail in the face of climate change. Ecological economics, which has been on the rise since the 1980s and works with the concept of entropy borrowed from physics, has not made any progress here either. If one understands environmental problems as disturbances of natural cycles (of water, carbon, nitrogen, etc.), then in dealing with them one will give preference to an economic theory that also regards the economic process as a material cycle. Piero Sraffa's theory, which follows on from the classical theory, is of this kind. It makes it possible to integrate the carbon cycle into an economic model that includes trading in emission rights with the participation of CO₂ sinks. The model shows that this trade does not generate extra profits, but cuts the profits of CO₂ emitters. It also shows that all CO₂-intensive products would have to be much more expensive in a CO₂-neutral economy than they are today.

A co-opetitive newsvendor model with product substitution and a wholesale price contract

When an original equipment manufacturer (OEM) sources key components from one contract manufacturer (CM), the CM may produce its own-brand product to compete against the OEM. Therefore, these two firms have a co-opetitive relationship. We develop a co-opetitive newsvendor model in which two newsvendors (OEM and CM) compete against each other in the format of product substitution. Moreover, the CM also serves as the only supplier to the OEM. We find that whether the CM’s final product is substitutable for the OEM’s product is the prerequisite condition that allows the CM to utilize its monopoly power in the key component market and earn extra profits. This result implies that being the only key component supplier of another newsvendor cannot automatically bring extra profits to the CM, except that the CM’s final product has a reasonable competitive advantage against the OEM’s final product. Furthermore, relative to the output of the purely competitive supply chain, the co-opetitive supply chain can achieve higher joint profits if the CM can fully compete against the OEM, i.e., the CM’s product can be treated as a perfect substitute for the OEM’s product. We also find that in the traditional selling to the newsvendor setting, when effective demand increases, the retailer (OEM) could be less profitable. Furthermore, we extend the discussion to the cases of horizontal decentralization and Nash bargaining. A parallel Cournot competition case is also discussed.