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In service systems with delay-sensitive customers, customer decisions to join the queue or balk influence demand, impacting service provider profits. Studies show that customers can be risk-seeking for short waits and risk-averse when waits exceed expectations. Prior research on this mixed-risk attitude is limited, focussing on optimal pricing policies from a social welfare perspective. This study fills this gap by investigating the impact of this behaviour on customer joining strategies and the provider's pricing and capacity policies. We analyse a profit-maximising firm managing an unobservable queue where customers display mixed-risk behaviour towards delay parameterised by a risk-switching point and a degree of risk propensity. Customers join or balk based on expected utility, while the firm determines the service price and rate to maximise expected profit. We derive optimal strategies for both customers and the firm under scenarios with concave or convex capacity costs. Computational experiments show that optimal pricing, capacity, and profit peak at intermediate risk-switching points. For smaller points, optimal price and capacity rise with the customers' degree of risk propensity, while larger points have minimal impact. Numerical exploration emphasises the significance of capacity cost and the effectiveness of leveraging price over controlling capacity for maximising firm profitability. [ABSTRACT FROM AUTHOR]

Fifty years ago, the Federal Trade Commission stopped enforcing its fictitious reference pricing guidelines, emphasizing the search qualities of price and the belief that competition would drive out deceptive behavior. Yet this practice of posting false, inflated comparison prices alongside sale prices has proliferated. Building on prior analytic work and the documented effects of reference pricing on search behavior and consumer choice, the authors develop a descriptive model explaining why fictitious reference pricing has spread instead of being extinguished by competition. After summarizing the model with a series of generalizations, the authors consider potential regulatory solutions to the problem. They propose that disclosure of the true normal price charged may be the only solution that could plausibly influence both consumer and firm behavior. Then, based on the existing literature, interviews with practitioners and regulators, an analysis of other nations' approaches, and the results of a laboratory study of 900 consumers to examine how they integrate "true normal price" information into deal evaluations, the authors develop a set of propositions about the likely effects of requiring firms to disclose recent selling prices for goods, identifying both potential benefits and challenges associated with such a requirement. [ABSTRACT FROM AUTHOR]

This article examines the role of policy entrepreneurs in countering regulatory capture, a phenomenon whereby regulatory bodies influenced by industry lobbying often prioritize private over public interests. The study employs an abductive process‐tracing approach to investigate the 2013 drug pricing reform in Morocco, illustrating how substantial policy shifts can occur even in authoritarian contexts susceptible to regulatory capture. The findings underscore the pivotal role of Houcine El Ouardi, the former Minister of Health, whose strategic leadership exemplified policy entrepreneurship. His capacity to navigate and surmount industry resistance was instrumental to the reform's success, culminating in a significant reduction in drug prices. This case challenges conventional wisdom regarding regulatory capture, demonstrating that individual agency can reshape regulatory outcomes despite opposition. By elucidating how policy entrepreneurs can drive transformative change in resistant regulatory environments under authoritarian regimes, the study contributes to the literature on policy entrepreneurship and regulation. [ABSTRACT FROM AUTHOR]

Background: Germany was the first country worldwide to offer mobile digital health applications (mHealth apps, "DiGA") on prescription with full cost coverage by statutory health insurances. Especially statutory health insurances criticize the current pricing and payment regulations in Germany due to "free and non-transparent" pricing in the first year and lack of cost use evidence. The study consists of two parts: The first part evaluates interests of digital health application providers and statutory health insurances in Germany to identify overlaps and divergences of interests. The second part includes the development of a comprehensive pricing and payment taxonomy for reimbursable mHealth apps in general. Methods: Both parts of the study used the input from 16 expert interviews with representatives of digital health application providers and statutory health insurances in Germany. In part one the authors conducted a qualitative content analysis and in part two they followed the taxonomy development process according to Nickerson et al. (2013). Results: A value based care model is expected to bring the greatest benefit for patients while statutory health insurances welcome the idea of usage based pricing. The final pricing and payment taxonomy consists of four design and negotiation steps (price finding, payment prerequisites, payment modalities, composition of negotiation board). Conclusions: As healthcare resources are scarce and thus need to be optimally allocated, it is important to implement pricing and payment terms for reimbursable mHealth apps that result in the greatest benefit for patients. To the best of the authors' knowledge, there has been no structured study yet that examines alternative pricing strategies for reimbursable mHealth apps.The developed pricing and payment taxonomy for reimbursable mHealth apps serves as planning and decision basis for developers, health policy makers and payers internationally. [ABSTRACT FROM AUTHOR]

The escalating use of artificial intelligence in marketing significantly impacts all aspects of consumer life. This research, grounded in attribution theory and S–O-R theory, employs scenario-based experimental methods to simulate two distinct purchasing contexts. The aim is to investigate consumers' psychological and behavioral responses to AI-initiated pricing. Through SPSS analysis of variance and Bootstrap analysis, the mechanisms of influence of AI-initiated pricing on consumer behavior are tested, revealing the mediating variables of mind perception and consumer perceived ethicality, as well as the mediating variables of perceived enterprise control. Data were collected from Chinese customers to test the model of this study. A total of 841 valid questionnaires were analyzed using ANOVA and Bootstrap analysis with SPSS. The results show that: (1) Consumers exhibit higher repurchase and word-of-mouth recommendation behaviors and lower complaint and switching behaviors for AI-initiated pricing compared to marketers; (2) AI-initiated pricing leads to diminished mind perceptions and augmented ethical perceptions among consumers. Ethical perceptions serve as a complete mediator, while mind perceptions play a less significant mediating role; (3) Perceived enterprise control plays a moderating role in the impact of AI-initiated pricing on consumer behavior. That is, when consumers know that the enterprise can control pricing agents, AI-initiated pricing leads to lower repurchase and word-of-mouth recommendation behaviors, and higher instances of complaining and switching behaviors than humans. [ABSTRACT FROM AUTHOR]

Introduction: Since 2011, the prices for all new drugs in Germany are negotiated based on a benefit assessment. The purpose of this study was to analyze the price regulation of drugs with unproven additional benefit. Methods: Benefit assessment procedures from 2011 to 2020 were reviewed and selected through AMNOG Monitor and Lauer Taxe. Negotiated annual therapy costs, the annual costs of the most cost-efficient appropriate comparative therapy (ACT) and the potential budget impact for 33 included procedures were calculated. Results: 55% of the included drugs achieved a negotiated price higher than the most cost-efficient ACT, 3% were identified as equal and 42% showed lower negotiated prices. The potential savings exceeded expenditures by around EUR 523.5 m. After price flexibility was adopted by the legislator in 2017, the overall potential savings still outweighed the expenditures by around EUR 62 m. Conclusions: Our analysis shows that making price negotiations more flexible by law does not undermine the fundamental aim of the AMNOG, which is to avoid additional expenditure without increased patient benefit. The regulation can thus fulfill the objective provided by the legislature of keeping drugs without proven additional benefits in the German healthcare system. [ABSTRACT FROM AUTHOR]

In choosing healthcare services, price and waiting time are two important factors that matter to patients. Price is set by healthcare providers, while waiting time is usually endogenously determined by patient choice and the healthcare provider's capacity investment. We study the pricing and capacity design for profit-driven hospitals offering two types of healthcare services—regular and premium—serving heterogeneous patients who choose from either of the two types of services. Patients make their choices based on both price and endogenously determined equilibrium waiting time. We then benchmark profit-driven hospitals to welfare-driven hospitals to reveal how the behaviors of for-profit hospitals deviate from the socially optimal outcomes in patients waiting, service capacity, and price. We find that fewer patients are treated by premium services in profit-driven hospitals, and thus profit-driven hospitals invest less in premium service capacity and charge a higher premium for premium services than welfare-driven hospitals. These inefficiency distortions exist in profit-driven hospitals primarily because they are incentivized to differentiate between the waiting times of the two types of service to induce patients to pay a higher premium for premium services. Our results also show that if the inefficiency in patient partition is corrected, profit-driven hospitals would choose the welfare-maximizing level of premium service capacity and thus achieve socially optimal results. However, we also find that regulations such as price ceiling and capacity regulation cannot fully correct the inefficiency in patient partition and capacity decisions of profit-driven hospitals. Lastly, the model is extended in several ways to ensure robustness. [ABSTRACT FROM AUTHOR]

I discuss private and central-bank-issued digital currencies, summarizing my prior research. I argue that prices of private digital currencies such as bitcoin follow random walks or, more generally, risk-adjusted martingales. For central bank digital currencies, I argue that they enhance the trilemma facing a central bank. Of the three objectives, price stability, efficiency, and monetary trust, the central bak can achieve at most two. [ABSTRACT FROM AUTHOR]

We report experimental and quasi-experimental evidence from a "sharing economy" marketplace that transitioned from decentralized to centralized pricing. Centralized pricing increased the utilization of providers' assets, resulting in higher revenues but also higher transaction costs. Providers who were barred from accessing the price system made nonprice adjustments, including reducing the availability of their assets, canceling booked transactions, and exiting the market. Providers who retained partial pricing control reacted substantially less but experienced similar revenue increases. We highlight the challenges of implementing centralized pricing and assessing its welfare effects. We show that partial control can mitigate these challenges, allowing providers to express their private and heterogeneous preferences while maintaining the benefits of centralization. This paper was accepted by Gabriel Weintraub, revenue management and market analytics. Funding: S. Jagabathula was funded in part by the Division of Civil, Mechanical, and Manufacturing Innovation [Grant 1454310]. Supplemental Material: The data files and online appendices are available at https://doi.org/10.1287/mnsc.2023.4789. [ABSTRACT FROM AUTHOR]

This editorial summarizes the papers in issue 18(2) (2023). The first paper extends the Solow–Swan growth model with spatial dependence, pollution and time delay. The second paper investigates the (mis)match between relative factor costs and the output elasticities of production factors due to innovations in the European Union's Smart Specialisation Strategy (S3). The third paper studies whether and in what way price regulation of gasoline affects competition and collusion between gasoline stations. The fourth paper provides empirical evidence that public library programmes encourage labour force participation in underdeveloped regions. The fifth paper proposes a general nesting spatial stochastic frontier model and a maximum likelihood estimation procedure to determine inefficiencies across units of observations. The sixth paper proposes a dynamic spatial autoregressive model in which the overall spatial weight matrix is composed of a convex combination of multiple underlying spatial weight matrices and the coefficients of all regressors are heterogeneous. [ABSTRACT FROM AUTHOR]

Abstract Background Extremely high prices facilitate drug development for ultra-rare diseases (ultra-orphan drugs). However, various problems arise in terms of healthcare financing and fairness, and the status of ultra-orphan drug pricing remains ambiguous. In this study, we investigated ultra-orphan drug prices in Japan relative to that of other drugs. We examined the relationship between annual expected drug prices and expected sales, and the expected number of patients, for 393 drugs containing new active ingredients for therapeutic use that were listed on the National Health Insurance drug price list in Japan between April 16, 2010 and August 26, 2020. In addition, we compared prices, the drug price calculation method, and price calculation adjustment factors for ultra-orphan and other drugs. Results Drug prices tended to increase as the expected number of patients to whom the drug was administered decreased; however, this trend diminished when the expected number of patients was less than 1000. On the other hand, the expected sales tended to decrease as the number of expected patients decreased, and this tendency was reinforced when the expected number of patients was less than 1000. The cost accounting method tended to be used for the price calculation of ultra-orphan drugs, but there were no price differences based on the drug price calculation method. Regarding the price calculation adjustment factors, the premium for usefulness tended to be higher for ultra-orphan drugs. The premium for marketability was higher for non-orphan drugs but did not differ from that for orphan drugs, except for ultra-orphan drugs. Conclusions The status of drug prices and expected sales differed beyond a threshold of 1000 expected patients, indicating that recovering the development cost for ultra-orphan drugs is difficult. In addition, the higher premium for usefulness for ultra-orphan drugs reflects the largely unmet need of the associated diseases. Scarcity among orphan drugs is not considered for marketability, highlighting the need for a new framework to promote the development of ultra-orphan drugs.

This article examines competing economic theories of crime and punishment within a common analytical framework. The theories—due to Becker (1968), Posner (1985) , and Adelstein (1981) —share the view of crime as exchange, but differ in the interpretation of punishment; specifically, is it aimed at pricing crime, preventing crime, or achieving corrective justice? The hybrid model used to address this question, originally developed by Hylton (2005) , explicitly incorporates market exchange as an alternative to criminal exchange. The results show that the optimal enforcement policy generally involves maximal punishment (however that is defined), but the optimal probability of apprehension can be high or low, depending on the parameters of the model. In the latter case, crime may completely crowd out the market. (JEL K14, K42) [ABSTRACT FROM AUTHOR]

Introduction: The transparency of data on the value chain of medicines is crucial for the study and monitoring of the pharmaceutical system. These data may impact medicine pricing negotiations, contribute to patient access to pharmaceutical products, and strengthen health systems. Objective: This study analyzed the national strategies to ensure the transparency of data from medicine cost development to marketing in Argentina, Brazil, and Colombia. Method: A descriptive study was carried out by searching databases, reports, documents, and scientific articles published between January and August 2022 related to rules on transparency and databases, including 1) marketing authorization; 2) pricing; 3) intellectual property; 4) clinical trials; 5) research and development (R&D); and 6) health technology assessment (HTA) of selected biopharmaceuticals. Results: Transparency data, rules, and information are not uniform. The infostructures (organizational capacity for collecting and distributing information) regarding the pharmaceutical value chain in these three countries face limitations in appropriate measures to publicly share data and evidence, including pre-clinical data, clinical data, and costs. None of the countries require transparency about data on research and development costs. All three countries present similar publicization of data on marketing authorization and intellectual property, with some differences. The significant limitations in Argentina include the absence of formal price regulation and data on the volume of medicine purchased and respective amounts paid. Among the three countries, Brazil showed a higher degree of information transparency, perhaps due to the legal regulation that guarantees citizens access to information of public interest. Brazil also stands out in terms of the public availability of HTA reports and pricing, in addition to the highest volume of information. In contrast, Colombia has in place a decree that allows 5 years of trial data exclusivity for new medicines, an act contrary to data transparency. Despite the different stages of transparency, no country has evidenced a robust use of these data in public policy decision-making. Conclusion: The results reinforce the presence of information asymmetry between stakeholders, data fragmentation, data gaps and overlap, and difficulty in comparing available data across the three countries and the use of these data nationally to produce evidence. [ABSTRACT FROM AUTHOR]

Recently, utilizing appropriate inventory control policy and determining the optimal selling price for various goods has been the main topic of scientific and industrial research. Inventory management policy 1 by the seller is one solution that improves the chain's performance by creating coordination between members of the supply chain. The current study attempts to devise an integrated model of inventory pricing and control under the inventory management policy by the seller for perishable goods with shortages is considered. The purpose of presenting the model is to determine the optimal price, the optimal repayment time, and the order size, in order to maximize the profit. To acquire those optimal values, the profit functions of the buyer and the seller are taken into account. Given the results acquired, it is demonstrated that at any cost, the repayment time is unique and optimal. It is concluded that with the optimal recovery time available, the objective function is a concave function of price, and its optimal value is available. Furthermore, utilizing the inventory management policy by the seller could be a proper means to reducing retailer costs while raising their profit. [ABSTRACT FROM AUTHOR]

Background Pharmaceutical spending has been increasing rapidly for years and is higher than ever before. To control the rising costs, countries are implementing regulatory frameworks such as (internal) reference pricing, price cuts or generics substitution. Internal reference pricing establishes a reference price within a country which serves as the maximum level of reimbursement for a group of pharmaceuticals. Price setting in the German market is especially relevant for many European countries, which use Germany as a reference country for their own price setting. Methods We evaluate pharmaceutical price dynamics for not reference priced pharmaceuticals (NRPs) as well as for reference priced pharmaceuticals (RPs) in Germany—referring to the internal reference price system. 64,862 medication packs have been extracted from the German pharmaceutical pricing register Lauer-Taxe. For each pack, we extracted detailed data on the company, manufacturer rebates, pharmacy retail prices, reference prices, co-payments, import quotas, and discount agreements. We then investigated price setting and dynamics of NRPs vs. RPs for all 14 indication areas by ATC code level 1. Results The average manufacturer price per pack was 604.84€ for NRPs and 112.11€ for RPs. Similar differences were found for the wholesale price and the pharmacy retail price. The reference price was—as expected—0.00€ for NRPs, and 154.40€ for RPs. NRP packs were imported in 42.38%, while RP packs were imported only in 24.62%. Highest average pharmacy retail prices could be found in the therapeutic areas ‘antineoplastic and immunomodulating agents’ (1711.47€), ‘systemic hormonal preparations’ (1331.95€), and ‘blood and blood forming organs’ (1260.58€). We detected high fluctuations in pharmacy retail prices per indication, as well as for reference prices per indication. The indications with the highest number of reference price regulated medical packs are ‘cardiovascular system’, ‘musculo-skeletal system’, and ‘nervous system’. Highest co-payments were found in the indications ‘antineoplastic and immunomodulating agents’, ‘blood and blood forming organs’, and ‘antiinfectives for systemic use’. Conclusion Price setting and price dynamics vary substantially between NRP and RP medication packs. Further, we saw major differences across all indication areas as well as when comparing medication packs launched by top 20 pharma companies vs. the rest.

Background: Extremely high prices facilitate drug development for ultra-rare diseases (ultra-orphan drugs). However, various problems arise in terms of healthcare financing and fairness, and the status of ultra-orphan drug pricing remains ambiguous. In this study, we investigated ultra-orphan drug prices in Japan relative to that of other drugs. We examined the relationship between annual expected drug prices and expected sales, and the expected number of patients, for 393 drugs containing new active ingredients for therapeutic use that were listed on the National Health Insurance drug price list in Japan between April 16, 2010 and August 26, 2020. In addition, we compared prices, the drug price calculation method, and price calculation adjustment factors for ultra-orphan and other drugs.Results: Drug prices tended to increase as the expected number of patients to whom the drug was administered decreased; however, this trend diminished when the expected number of patients was less than 1000. On the other hand, the expected sales tended to decrease as the number of expected patients decreased, and this tendency was reinforced when the expected number of patients was less than 1000. The cost accounting method tended to be used for the price calculation of ultra-orphan drugs, but there were no price differences based on the drug price calculation method. Regarding the price calculation adjustment factors, the premium for usefulness tended to be higher for ultra-orphan drugs. The premium for marketability was higher for non-orphan drugs but did not differ from that for orphan drugs, except for ultra-orphan drugs.Conclusions: The status of drug prices and expected sales differed beyond a threshold of 1000 expected patients, indicating that recovering the development cost for ultra-orphan drugs is difficult. In addition, the higher premium for usefulness for ultra-orphan drugs reflects the largely unmet need of the associated diseases. Scarcity among orphan drugs is not considered for marketability, highlighting the need for a new framework to promote the development of ultra-orphan drugs. [ABSTRACT FROM AUTHOR]

Previous studies have confirmed that reference prices play an essential role in consumer purchasing decisions, and some researchers have suggested that reference prices are positively influenced by innovation. Therefore, we construct an interactive effect of innovation and reference price to study their combined impact on supply chain decisions. We model a supply chain, where a manufacturer determines the innovation level and the wholesale price while the retailer controls the retail price, as a dynamic Stackelberg game. We show that the interactive effect causes the steady-state wholesale and retail prices to increase, thus motivating the manufacturer to increase innovation investment. We see that the retail price and the level of innovation increase in reference price effect whereas they decrease in consumer memory. The centralized firm has a higher steady-state innovation level and innovation/price ratio and lower steady-state retail price compared to the decentralized supply chain. Consumers also benefit from the interactive effect as well as from centralization. Finally, we use numerical analysis to demonstrate our results and offer some managerial implications. [ABSTRACT FROM AUTHOR]

Background: Pharmaceutical spending has been increasing rapidly for years and is higher than ever before. To control the rising costs, countries are implementing regulatory frameworks such as (internal) reference pricing, price cuts or generics substitution. Internal reference pricing establishes a reference price within a country which serves as the maximum level of reimbursement for a group of pharmaceuticals. Price setting in the German market is especially relevant for many European countries, which use Germany as a reference country for their own price setting. Methods: We evaluate pharmaceutical price dynamics for not reference priced pharmaceuticals (NRPs) as well as for reference priced pharmaceuticals (RPs) in Germany—referring to the internal reference price system. 64,862 medication packs have been extracted from the German pharmaceutical pricing register Lauer-Taxe. For each pack, we extracted detailed data on the company, manufacturer rebates, pharmacy retail prices, reference prices, co-payments, import quotas, and discount agreements. We then investigated price setting and dynamics of NRPs vs. RPs for all 14 indication areas by ATC code level 1. Results: The average manufacturer price per pack was 604.84€ for NRPs and 112.11€ for RPs. Similar differences were found for the wholesale price and the pharmacy retail price. The reference price was—as expected—0.00€ for NRPs, and 154.40€ for RPs. NRP packs were imported in 42.38%, while RP packs were imported only in 24.62%. Highest average pharmacy retail prices could be found in the therapeutic areas 'antineoplastic and immunomodulating agents' (1711.47€), 'systemic hormonal preparations' (1331.95€), and 'blood and blood forming organs' (1260.58€). We detected high fluctuations in pharmacy retail prices per indication, as well as for reference prices per indication. The indications with the highest number of reference price regulated medical packs are 'cardiovascular system', 'musculo-skeletal system', and 'nervous system'. Highest co-payments were found in the indications 'antineoplastic and immunomodulating agents', 'blood and blood forming organs', and 'antiinfectives for systemic use'. Conclusion: Price setting and price dynamics vary substantially between NRP and RP medication packs. Further, we saw major differences across all indication areas as well as when comparing medication packs launched by top 20 pharma companies vs. the rest. [ABSTRACT FROM AUTHOR]

Point-of-care diagnostic tests for community-acquired acute respiratory tract infections (CA-ARTI) can support doctors by improving antibiotic prescribing. However, little is known about health technology assessment (HTA), pricing and funding policies for CA-ARTI diagnostics. Thus, this study investigated these policies for this group of devices applied in the outpatient setting in Europe. Experts from competent authority responded to a questionnaire in Q4/2020. Information is available for 17 countries. Studied countries do not base their pricing and funding decision for CA-ARTI diagnostics on an HTA. While a few countries impose price regulation for some publicly funded medical devices, the prices of CA-ARTI diagnostics are not directly regulated in any of the surveyed countries. Indirect price regulation through public procurement is applied in some countries. Reimbursement lists of medical devices eligible for public funding exist in several European countries, and in some countries these lists include CA-ARTI diagnostics. In a few countries, the public payer funds the health professional for performing the service of conducting the test. Given low levels of regulation and few incentives, the study findings suggest room for strengthening pricing and funding policies of CA-ARTI diagnostics to contribute to increased acceptance and use of these point-of-care tests. [ABSTRACT FROM AUTHOR]

The distribution of electric vehicle (EV) charging areas is affected by customers’ behaviors, which has strong temporal and spatial characteristics. Thus, some charging stations (CSs) are always busy, practically, whereas others are not, which leads to lower charging efficiency and profit. To solve this, a consumer-oriented charging incentive strategy for EVs in multiple regions is proposed, which can guide the transfer and alleviate the congestion of CSs so as to improve the economy of scheduling. In this article, by setting different charging prices in various regions, the price-based transfer model (PBTM) of EVs is constructed to describe price effects on transfer behaviors of EVs. Then, the PBTM is integrated into a stochastic scheduling scheme managed by the distribution system operator (DSO). Charging income and extra cost of line loss caused by charging are additionally considered to maximize the total profit of DSO when scheduling. Finally, the applicability and economic advantages of the proposed strategy are analyzed with different CSs’ capacities as well as users’ price sensitivity and regulation depth of EVs, and the influence of important parameters is investigated deeply. [ABSTRACT FROM AUTHOR]

Load aggregators (LAs) purchase demand response (DR) capacity from users by incentive compensation and then resell them by bidding in the day-ahead DR market to gain profits. Existing related research fails to adequately integrate bidding and pricing decision-makings and lacks sufficient consideration of uncertain user response behaviors, resulting in unstable trading returns. To this end, we propose a novel joint optimization method for bidding and pricing of the LA. First, a two-stage joint optimization framework is constructed to coordinate the temporally coupled bidding and pricing decisions, where these two strategies are simultaneously optimized to form the DA bidding strategy at first, and the pricing adjustment is then introduced after market-clearing to develop the formal user incentive scheme. Second, to account for the risks from uncertain response behaviors, the first stage incorporates DR settlement rules and the hedging effect of the aggregated response uncertainty to develop a relatively aggressive bidding strategy. After that, a user selection mechanism is then introduced to filter out users with both low response costs and reliable responses for participation. Numerical studies are presented to validate the proposed methodology in formulating optimal trading strategies that effectively tradeoff transaction revenue and risks. • The coupling impacts of bidding and pricing on profit are analyzed. • A two-stage framework is proposed to manage trading risks • Bidding and Pricing are jointly optimized to maximize profits. [ABSTRACT FROM AUTHOR]

On-demand trip sharing is an efficient solution to mitigate the negative externalities e-hailing has on traffic in a network. It motivates platform operators to reduce their fleet size and serves the same demand level with a lower effective distance traveled. Users nevertheless prefer to travel solo and for shorter distances, despite the price discount they receive. By offering them the choice to pool and travel in high-occupancy dedicated bus lanes, we provide them with a larger incentive to share their rides, yet this creates additional bus delays. In this work, we develop dynamic feedback-based control policies that regulate pool vehicle access to bus lanes by adjusting the price gap between solo and pool trips, with the aim of improving multi-modal delays and providing better utilization of network capacity. First, we develop a modal- and occupancy-dependent aggregate model for private vehicles, ride-pooling, and buses based on network production, and we use this model to test different control strategies. To minimize the error between the target and actual speeds in the bus network, we design a PI controller and show that by adjusting pool trip fares, we can, with little input data, minimize this error. We also put forward a Model Predictive Control (MPC) framework to minimize the total Passenger Hours Traveled (PHT) and Waiting Times (WT) for the different travelers. Moreover, we show how the MPC framework can be utilized to impose a minimum speed in dedicated bus lanes and ensure that buses operate on schedule. The results demonstrate the possibility of improving the overall network conditions by incentivizing or discouraging pooling in the vehicle or bus network. • Proposed an occupancy-dependent multi-modal vehicle allocation strategy. • Advanced a dynamic macroscopic modeling framework for the allocation strategy. • Developed a control scheme for pricing pool ride-hailing trips in bus lanes. • Compared multi-modal network delays under PI and MPC pool pricing control frameworks. • Investigated the potential of the strategy to improve delays compared to exclusive bus lanes. [ABSTRACT FROM AUTHOR]

• Creating integrity in the health system. • Cooperation between Private and Public Components and optimal use of the available capacities in this system with bilevel programming. • Price control of health services. • Increase transparency in the country. • Categorizing Patients and Controlling Budget Costs. The importance of health systems for societies makes it necessary to examine them from a scientific perspective and improve healthcare. Healthcare service prices determine patients' decisions, so setting them correctly is crucial to creating balance in the system. In this research, we propose a bi-level model that includes private providers and the government to suggest optimal prices for healthcare services. The pricing method is suggested based on service quality and patient waiting time, and patients are categorized in two ways: 1) by the severity of their disease and the urgency of their condition, and 2) by their income and sensitivity to service prices. We aim to maximize service providers' profit at an optimal price while maximizing patient satisfaction. To achieve maximum patient utility, the government proposes contracts that increase overall societal utility. This research proposes and compares four cases: non-contract, cost-sharing contract, subsidy contract, and differentiated subsidy contract. Based on Stackelberg's game theory, we consider the government the leader and the private service provider the follower. Numerical results of the research show that the cost-sharing contract allocates support to all patients in society, but it does not achieve significant utility for the whole society, despite covering more patients. The subsidy contract allocates a more significant amount of subsidy to fewer patients and covers only those with an urgent condition. Differentiated subsidy contracts allocate subsidies according to price-sensitive groups, resulting in better use of budget expenditures. The managerial insight of this research, leads managers to consider contracts. [ABSTRACT FROM AUTHOR]

The unanticipated global mass panic that has arisen as a result of the rapid spread of the COVID-19 has had a major impact on the functioning of many markets. Many competition authorities around the world have faced with excessive pricing practices due to the dramatic price hikes of essential items, ranging from personal and medical equipment to basic food products particularly at the onset of the pandemic. The crisis has not been just about pricing, whether the public or the state is willing to pay for certain products or not; at the heart of the problem, there has been a sudden sharp asymmetry between the supply and demand. Based on this asymmetry, this article, by acknowledging that Article 102 (a) fails to deliver a swift and efficient response to this crisis due to conceptual and practical difficulties in its application, addresses other ways that competition authorities and governments use to deal with the virus-profiteers. [ABSTRACT FROM AUTHOR]

Airlines apply the revenue management techniques of dynamic pricing and capacity control to maximize revenue. Traditional capacity control techniques assume that the airlines offer only specific products to customers, i.e. departure and arrival date and times are fixed. However, airlines may also offer flexible products by which, a passenger will come to know about the departure time at a later time and not while booking tickets. Flexible products though discussed in literature are not well researched and in this work an attempt is being made to address this literature gap. We develop a new class of product called flexible products with preferences; this class can be thought of as intermediate between specific and flexible products. These products are designed for customers who are flexible about the departure times but have preferences among them. We focus on the development of capacity control techniques when flexible products (including flexible products with preferences) are offered along with specific products. We develop a heuristic to determine a booking and seat allocation policy for all forms of flexible products. Such flexible products sold at lower prices will lead to more demand induction at the expense of cannibalizing the potential high fare demand. Hence we also evaluate the effect of demand induction and cannibalization on the capacity control and the revenue generated by the introduction of all forms of flexible products. Simulation experiments are performed to illustrate the techniques developed. [ABSTRACT FROM AUTHOR]

When planning for the introduction of a stream of new products into the marketplace, managers must consider both the timing and dynamic pricing decisions to determine an appropriate entry strategy into the marketplace. Literature in new product development (NPD) typically addresses optimal timing and pricing decisions independently. We develop an analytical model of coordinated product timing and pricing decisions when there are two generations of a new product under consideration. Factors driving the timing and pricing decisions include the unit sales and cost relationships for each generation as well as NPD costs for introducing the next generation of products. We derive analytic results that characterise the optimal timing and pricing strategies for a single product rollover scenario. We analyse several numerical examples to illustrate the interplay between optimal pricing and time-to-market strategies under more general settings. [ABSTRACT FROM PUBLISHER]

We study a transportation network company (TNC) that offers on-demand solo and pooling e-hail services in an aggregate mobility service market, while competing with transit for passengers. The market equilibrium is established based on a spatial driver–passenger matching model that determines the passenger wait time for both solo and pooling rides. We prove, under mild conditions, this system always has an equilibrium solution. Built on the market equilibrium, three variants of pricing problems are analyzed and compared, namely, (i) profit maximization, (ii) profit maximization subject to regulatory constraints, and (iii) social welfare maximization subject to a revenue-neutral constraint. A comprehensive case study is constructed using TNC data collected in the city of Chicago. We found pooling is desirable when demand is high but supply is scarce. However, its benefit diminishes quickly as the average en-route detour time (i.e., the difference between the average duration of solo and pooling trips) increases. Without regulations, a mixed strategy—providing both solo and pooling rides—not only achieves the highest profit and trip production in most scenarios, but also gains higher social welfare. The minimum wage policy can improve social welfare in the short term. However, in the long run, the TNC could react by limiting the size of the driver pool, and consequently, render the policy counterproductive, even pushing social welfare below the unregulated level. Moreover, by maintaining the supply and demand of ride-hail at an artificially high level, the minimum wage policy tends to exacerbate traffic congestion by depressing the use of collective modes (transit and pooling). A congestion tax policy that penalizes solo rides promotes pooling, but may harm social welfare. However, it promises to increase both social welfare and pooling ratio when jointly implemented with the minimum wage policy. • We study a transportation network company that offers solo and pooling e-hail services and competes with transit. • The market equilibrium is established based on a novel spatial driver–passenger matching model. • We analyze the platform's pricing strategies under various objectives and regulatory constraints. • The minimum wage policy can improve social welfare in the short term but could be harmful in the long run. • A congestion tax policy that penalizes solo rides promotes pooling, but may harm social welfare. [ABSTRACT FROM AUTHOR]

Although pricing and inventory control are crucial decisions in each production system, these decisions are usually investigated separately. This paper considers pricing and inventory control decisions simultaneously in a hybrid production system. The hybrid production system has two recovery options, remanufacturing and refurbishing sites. The demand follows Poisson distribution, which depends on the sale price of each product. Returned products arrive according to a Poisson process. Each returned product can be remanufactured, refurbished, or disposed. The time to manufacturing, refurbishing, and remanufacturing a product also follows an exponential distribution. By modeling the system as a Markov chain, the long-run expected profit function is obtained in terms of the dispose-down-to level of returned products and the order-up-to level and the sale price of serviceable products. A three-dimensional state space of the Markov Chain dependent to the sale price is developed considering pricing and inventory control decisions simultaneously with remanufacturing and refurbishing returned products. Since the model is a mixed integer nonlinear programming and known as complex models, the Artificial Bee Colony (ABC) algorithm, simulation and complete search method are used to solve the problem. The results show that by increasing the purchase price of the returned products, the amount of returned products will increase. If the refurbishing cost of the returned products is high or the disposal cost is low, less inventory should be kept in the system with a high price of serviceable products. If the lost sale cost is high, the more inventory should be maintained. Moreover, by decreasing the price elasticity of demand, the customer's demand increases, and then more inventory should be maintained in the system. [ABSTRACT FROM AUTHOR]

A repeated challenge in launching a two-sided market platform is how to ignite the cross-side network effects to jump-start adoption. This research note studies "piggybacking"—expanding the focal market to recruit exclusive users from external networks—as a new and nonpricing control to launch platforms in conjunction with pricing controls. We first consider consumer-side piggybacking. Our results provide a rich set of novel insights into strategies that platforms use to monetize exclusive access to external users with nontrivial characterizations of the interplay among piggybacking, cross-side network effects, and price competition. We identify conditions when piggybacking is profit improving and when it leads to a prisoner's dilemma, depending on the piggybacking cost and strengths of cross-side network effects. Among others, we show that piggybacking may intensify rather than ease price competition. We then consider provider-side piggybacking, and we show that the insights are qualitatively the same as consumer-side piggybacking except that the prisoner's dilemma disappears if piggybacking providers multihome. A repeated challenge in launching a two-sided market platform is how to ignite the cross-side network effects to jump-start adoption. Prior literature often addresses this issue by using pricing controls—a high price on one side to raise the margin and a low price on the other to attract users—or the "seesaw principle." More recently, platforms are increasingly embracing nonpricing controls to accelerate user adoptions. Little is known, however, about the role of nonpricing controls and their interplay with pricing controls. In this research note, using a game-theoretic framework, we study "piggybacking"—that is, expanding the focal market to recruit exclusive users from external networks—as a new and nonpricing control to launch platforms in conjunction with pricing controls. We first consider consumer-side piggybacking. In a standard "competitive bottlenecks" setting in which consumers single home and providers multihome, we provide a rich set of novel insights into strategies that platforms use to monetize exclusive access to external users with nontrivial characterizations of the interplay among piggybacking, cross-side network effects, and price competition. We identify necessary and sufficient conditions when piggybacking is profit improving and when it leads to a prisoner's dilemma, depending on the piggybacking cost and strengths of cross-side network effects. Among others, we show that, if the platforms' equilibrium strategies were to subsidize consumers (when provider-side network effects are stronger than consumer-side network effects), piggybacking may intensify rather than ease price competition. In contrast, if the platforms' equilibrium strategies were to subsidize providers (when provider-side network effects are weaker than consumer-side network effects), piggybacking may ease price competition. Interestingly, piggybacking reinforces the seesaw principle for the piggybacking platform. We provide a full characterization on such nontrivial equilibrium outcomes. We then consider provider-side piggybacking, and we show that the insights are qualitatively the same as consumer-side piggybacking except that the prisoner's dilemma disappears if piggybacking providers multihome. Managerial implications for platform practitioners are also discussed. [ABSTRACT FROM AUTHOR]

This paper introduces a practical supply chain optimisation model that incorporates both economic and carbon emission objectives. The proposed model is implemented to examine the possible economic and environmental trade-offs for various carbon-pricing and fuel-pricing scenarios in an actual case company representing the discrete, durable parts manufacturing sector. Analysis of the numerical results provides important managerial implications and policy insights. For industry practitioners, the findings can assist in identifying the critical activities along the supply chain on which to focus in order to minimise the cost implications of a carbon-pricing regulation. For related policy-makers, the findings provide insights on how carbon should be priced to make meaningful impacts on emissions reduction while matching variations in fuel prices. [ABSTRACT FROM PUBLISHER]

Abstract Background Out-of-pocket (OOP) payments can constitute a major barrier for affordable and equitable access to essential medicines. Household surveys in Kyrgyzstan pointed to a perceived growth in OOP payments for outpatient medicines, including those covered by the benefits package scheme (the Additional Drug Package, ADP). The study aimed to explore the extent of co-payments for ADP-listed medicines and to explain the reasons for developments. Methods A descriptive statistical analysis was performed on prices and volumes of prescribed ADP-listed medicines dispensed in pharmacies during 2013–2015 (1,041,777 prescriptions claimed, data provided by the Mandatory Health Insurance Fund). Additionally, data on the value and volume of imported medicines in 2013–2015 (obtained from the National Medicines Regulatory Agency) were analysed. Results In 2013–2015, co-payments for medicines dispensed under the ADP grew, on average, by 22.8%. Co-payments for ADP-listed medicines amounted to around 50% of a reimbursed baseline price, but as pharmacy retail prices were not regulated, co-payments tended to be higher in practice. The increase in co-payments coincided with a reduction in the number of prescriptions dispensed (by 14%) and an increase in average amounts reimbursed per prescription in nearly all therapeutic groups (by 22%) in the study period. While the decrease in prescriptions suggests possible underuse, as patients might forego filling prescriptions due to financial restraints, the growth in average amounts reimbursed could be an indication of inefficiencies in public funding. Variation between the regions suggests regional inequity. Devaluation of the national currency was observed, and the value of imported medicines increased by nearly 20%, whereas volumes of imports remained at around the same level in 2013–2015. Thus, patients and public procurers had to pay more for the same amount of medicines. Conclusions The findings suggest an increase in pharmacy retail prices as the major driver for higher co-payments. The national currency devaluation contributed to the price increases, and the absence of medicine price regulation aggravated the effects of the depreciation. It is recommended that Kyrgyzstan should introduce medicine price regulation and exemptions for low-income people from co-payments to ensure a more affordable and equitable access to medicines.

We consider an optimization problem for a dual-channel supply chain with one manufacturer and one retailer under stochastic demand. The manufacturer and retailer play a Stackelberg game. The manufacturer, acting as the leader, decides the total inventory capacity, wholesale price and selling price in the direct channel. The retailer, acting as the follower, decides the order quantity and retail price in the traditional channel. By solving the optimization problem, we find that given the selling price in the direct channel and wholesale price, the retailer's decisions on order quantity is similar to that for the newsvendor problem. Meanwhile, the manufacturer's decision on the inventory allocated to the direct channel also has the similar structure. Besides, we show that in our analysis framework, the retail price in the traditional channel, wholesale price and total inventory capacity can be presented in closed-forms. Finally, we numerically study the effects of the demand uncertainties and price sensitivities on the optimal solutions and performance. It is interesting to show that the retailer's expected profit may be unexpectedly increased when the demand variability in the traditional channel increases, due to the competition between two channels. [ABSTRACT FROM AUTHOR]

Pricing and inventory replenishment are important operations decisions for firms such as retailers. To make these decisions effectively, a firm needs to know the demand distribution and its dependency on selling price, which is usually estimated using sales data at various testing price levels. Although more testing prices can lead to a better estimation of the demand–price relationship, frequent price changes are costly and come with adverse effect such as customers' negative perception. In this article, data-driven algorithms are developed that learn the demand structure with constraints on the number of price changes. These algorithms are shown to converge to the optimal clairvoyant solution, and the convergence rates are the best possible in terms of profit loss. A firm makes pricing and inventory replenishment decisions for a product over T periods to maximize its expected total profit. Demand is random and price sensitive, and unsatisfied demands are lost and unobservable (censored demand). The firm knows the demand process up to some parameters and needs to learn them through pricing and inventory experimentation. However, because of business constraints, the firm is prevented from making frequent price changes, leading to correlated and dependent sales data. We develop data-driven algorithms by actively experimenting inventory and pricing decisions and construct maximum likelihood estimator with censored and correlated samples for parameter estimation. We analyze the algorithms using the T-period regret, defined as the profit loss of the algorithms over T periods compared with the clairvoyant optimal policy that knew the parameters a priori. For a so-called well-separated case, we show that the regret of our algorithm is O (T 1 / (m+1) ) when the number of price changes is limited by m ≥ 1 and is O (log T) when limited by β log T for some positive constant β > 0 , whereas for a more general case, the regret is O (T 1 / 2 ) when the underlying demand is bounded and O (T 1 / 2 ⁡ log T) when the underlying demand is unbounded. We further prove that our algorithm for each case is the best possible in the sense that its regret rate matches with the theoretical lower bound. [ABSTRACT FROM AUTHOR]

Introduction. The focus on transition to the input method of estimated cost accounting, demonstrated by the leaders of the construction industry, outlines the principal goals pursued in the process of improving the pricing system. The monitoring of prices for construction resources gains in importance. The research is based on the analysis of the construction industry’s current need for updated regulatory information and an improved pricing methodology. Materials and methods. A relevant problem of pricing, which is now quality-driven, has been solved by the construction industry amidst the strengthening role of government agencies. Presently, pricing is driven by the factors that characterize the course of an investment process, primarily, promoted by the customer. This methodology encompasses the assessment of pricing regulations with a required extent of generalization in terms of any submitted data. Results. The experiment conducted to assess the established pricing regulations in terms of special construction facilities has proven the maximal significance of factors, describing a construction project stage as a correlation between estimated and actual costs incurred by a construction company. Against the background of impeded introduction of changes into costing standards, a pool of solutions has been generated to monitor prices for construction resources and to generate price escalation models. Conclusions. The best methods used to adapt standard prices to actual costs of construction products should involve the monitoring of prices for the whole range of construction resources. Methodological problems are to be solved in a way that must improve the trustworthiness of estimated construction costs. The novelty and practical significance of this research stem from the analysis of the current development stage of the system of federal and industry-specific regulations and methodologies. [ABSTRACT FROM AUTHOR]

• Studies a temporary price increase dynamic pricing, for a non-perishable product. • Develops a continuous joint replenishment and pricing decisions policy. • Solves for the optimal replenishment and pricing policy parameters. • Runs simulation for a large number of problem instances. • Performs extensive sensitivity analyses. Pricing and inventory management make up together revenue management, which is a significant effort to boost revenues out of available resources. Firms use various forms of dynamic pricing, including personalized pricing, markdowns, promotions, coupons, discounts, and clearance sales, to respond to market fluctuations and demand uncertainty. In this paper, we study a temporary price increase policy, a form of dynamic pricing, for a non-perishable product, a practice used by several giant retailers such as Amazon, Walmart, and Apple. We develop a continuous review inventory model that allows for joint replenishment and pricing decisions, where the lead time is not zero. A replenishment decision controls supply, while a pricing decision controls demand. A manager exercises a temporary price increase to slow demand and avoid a stock-out situation while waiting for a shipment, which may not necessarily increase revenues, but decrease stock-out costs. The problem is to solve for the optimal replenishment and the pricing policy parameters that maximize the long-run expected profit. That is, when and how much to order and when to raise the price. In this paper, the inventory level and time trigger a price increase. We solve many numerical examples and perform extensive sensitivity analyses. Our results show that compared to a model that focuses on fixed pricing, our model brings an additional increase in profit of about 13%. [ABSTRACT FROM AUTHOR]

We consider the problem of strategic competition management on the markets of high-tech industry. We take into account that an aggressive pricing policy in the long run can lead to suppliers leaving the market, reducing its competitiveness and increasing purchase prices. To optimize the pricing policy of customers while accounting for this effect, we propose a model of bilateral oligopoly as a closed queuing system. [ABSTRACT FROM AUTHOR]

This article presents a deterministic model for jointly optimising pricing and inventory control of a perishable product subject to both physical deterioration and freshness condition degradation. The demand for the product depends on its price, the current inventory level and the freshness condition. Our model allows for any positive amount of end-of-cycle inventory. Conditions for the existence and uniqueness of an optimal solution of the model are developed and an algorithm is suggested to find the optimal values of the price, the cycle length, the order quantity, and the end-of-cycle inventory. Then, numerical examples are given, and sensitivity analysis is performed. Our study contributes to satisfying the need for inventory models that consider simultaneous physical deterioration and freshness degradation of perishable products along with price-, age- and stock-dependent demand. [ABSTRACT FROM AUTHOR]

The literature has recognized that the consumers' purchase behaviour and retailers' policies are significantly influenced by reference price effects, but has yet to provide flexible operational decisions on the threshold-based reference price. In this study, we consider an infinite-horizon joint pricing and inventory control problem in which the customers' psychological behaviour is modelled as reference price effects and price thresholds. Specifically, there is a region of price insensitivity allowing for threshold effects around the reference price, which is formulated as a three-regime piecewise function with the consideration of gain, loss, and indifference. A resolution approach based on proximal policy optimization is proposed to address the combinatorial complexity of continuous domains in action-state spaces. Tested on eight different market environments, we demonstrate how the deep reinforcement learning (DRL) approaches the ground-truth algorithm and outperforms three other algorithms. Moreover, near-optimal strategies and convergence results are obtained with regard to initial states and price thresholds of the system. The results show that the order-up-to level is increasing in price thresholds and the sales price is decreasing in them, while the retailer's profits suffer from the increase in thresholds. Besides, the sales price is increasing in the reference price. In the steady state of the environment, the average profits are higher than those in which the retailer ignores reference price effects with thresholds. Our study provides evidence that black-box DRL algorithms can effectively solve joint pricing and inventory control problems with psychologic and behavioural concerns. [ABSTRACT FROM AUTHOR]

Behavioral pricing research has shown consumers to have lower and upper price thresholds, represented by an inverted U-shaped price acceptability function. We propose another basic reaction to price, namely, "lower price is better," represented by a decreasing acceptability function without a lower price threshold. A set of variables is hypothesized to predict consumer reaction to price. Price consciousness, price-quality relation, and product involvement are shown to influence the shape of the price acceptability function. A procedure and model to scale price acceptability and obtain acceptability functions are introduced and applied. The cumulative results suggest reliable acceptability scales along with evidence for convergent and construct validity. [ABSTRACT FROM AUTHOR]

We use a unique set of equities in the when-issued market to provide new tests of the law of one price in financial markets. We compare the prices of when-issued and regular way shares of publicly traded subsidiaries and their parents around the time the subsidiaries are fully divested and we find that the when-issued shares of the subsidiary trade at a discount. Pricing differences stem from measurement factors such as exchange location and bid-ask clustering that bias the observed when-issued pricing differential away from zero. The remaining difference is due to asymmetric movements in bid and ask quotes in the two markets. We also find evidence of temporary price pressures on the date of execution of the spinoff of the subsidiary firms that bear resemblance to the pricing in the when-issued market. We interpret the evidence as consistent with the law of one price in the presence of transaction costs and microstructure phenomena. [ABSTRACT FROM AUTHOR]

The notion of reference price is becoming more popular in modelling price effects on consumers' purchasing behaviour. In order to understand the formation of reference price, an integrative analysis of the different concepts of reference price is proposed here. We present a classification of some twenty-six different concepts of reference price, based on an analysis of the different cognitive processes involved in the different conceptualisations. In addition, similarities and differences between the different concepts are examined. Finally, we consider utilization of particular reference price concepts in reference price modelling as well as in managerial decisions pertinent to various market situations. [ABSTRACT FROM AUTHOR]

In this article, the authors expand traditional channel control models to investigate the value of absorbing pricing decisions within an exporter's decision-making domain. From a governance perspective, pricing control is considered a structured continuum driven by factors both internal and external to the firm. More specifically, the authors investigate the organizational and environmental influences driving pricing control decisions and the impact of pricing control on both the economic and strategic performance of the firm. Using linear and moderated regression analysis, the authors find that both the strategic perspectives and the organizational characteristics of exporters significantly influence pricing control, yet in ways counter-intuitive to traditional thinking. Similarly, the performance implications add new insight to the value of pricing control in dynamic overseas environments. The authors discuss managerial and research implications. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue including one by Matthew B. Myers and Michael Harvey about pricing controls in export channels.

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• We present an inventory control model for a supply chain of deteriorating items. • We adopt the probabilistic demand and deterioration functions. • We develop and compare integrated and non-integrated inventory control policy. • We study the impact of the compensation policy in the supply chain coordination. • We perform sensitivity analysis and simulation to illustrate the model's results. This study addresses the problem of inventory control and pricing in a three-echelon supply chain (SC) with deteriorating items. It is assumed that deterioration and demand and functions of the manufacturer and retailer are probabilistic, and relationship between SC members is according to the "delayed equal-sized shipment inventory policy". One integrated policy and three non-integrated ones are formulated, and the conditions to obtain the solution are discussed. Through the simulation and sensitivity analysis on an extended numerical example, some managerial implications are presented. Moreover, a compensation policy is used for evaluation of the benefits and losses related to non-integrated policies. [ABSTRACT FROM AUTHOR]

The Paris Agreement requires mitigation contributions from all Parties. Therefore, the determination of additionality of activities under the market mechanisms of its Article 6 will need to be revisited. This paper provides recommendations on how to operationalize additionality under Article 6. We first review generic definitions of additionality and current approaches for testing of additionality before discussing under which conditions additionality testing of specific activities or policies is still necessary under the new context of the Paris Agreement, that is, in order to prevent increases of global emissions. We argue that the possibility of 'hot air' generation under nationally-determined contributions (NDCs) requires an independent check of the NDC's ambition. If the NDC of the transferring country does contain 'hot air', or if the transferred emission reductions are not covered by the NDC, a dedicated additionality test should be required. While additionality tests of projects and programmes could continue to be done through investment analysis, for policy instruments new approaches are required. They should be differentiated according to type of policy instrument. For regulation, we suggest calculating the resulting pay-back period for technology users. If the regulation generates investments exceeding a payback period threshold, it could be deemed additional. Similarly, carbon pricing policies that generate a carbon price exceeding a threshold could qualify; for trading schemes an absence of over-allocation needs to be shown. The threshold should be differentiated according to country categories and rise over time. Key policy insights Without additionality testing, market mechanisms under the Paris Agreements might lead to an international diffusion of 'hot air'. To avoid this, an independent assessment of NDC ambition is in order. Otherwise, activities under the mechanisms need to undergo specific additionality tests. Additionality testing of projects and programmes should build on the experience developed under the Kyoto Protocol mechanisms. Bold approaches are needed for assessing additionality of policies. To avoid cumbersome assessment of all activities triggered by such policies, highly aggregated approaches are suggested, ranging from payback period thresholds for technologies mandated by regulation to minimum price levels triggered by carbon pricing policies. Over time, the stringency of threshold values should increase. [ABSTRACT FROM AUTHOR]

This paper examines the issue of price and advertising coordination in bilateral monopolies from a dynamic perspective. Its main objectives are to design incentive mechanisms that the manufacturer can use in order to reduce double marginalization, and to investigate whether these mechanisms can be implemented by the manufacturer and accepted by the retailer. I consider a differential game where a manufacturer controls its wholesale price and its national advertising effort. The carry‐over effects of national advertising build up brand goodwill, which represents the model's state variable. The retailer controls the product's retail price and the local advertising effort, which affect consumer demand, in conjunction with the brand goodwill. I compute strategies and outcomes under three scenarios: (a) a fully coordinated scenario where channel members act as if the channel was vertically integrated; (b) a noncoordinated scenario, considered as the status quo, where the channel is decentralized; and (c) a scenario where incentive mechanisms are offered by the manufacturer. The main results indicate that two incentive mechanisms, namely, a retail‐price incentive and an advertising allowance offered by the manufacturer to the retailer can mitigate the double‐marginalization problem. With these incentives, and an appropriate choice of the channel‐coordinating wholesale price, the manufacturer can induce the retailer to fix its control variables at their channel‐coordinating levels without committing to implement the channel‐coordinating level of national advertising. Our results highlight the role of the channel‐coordinating wholesale price level on the Pareto‐optimality and the implementation of the incentives. I compute the values for the channel‐coordinating wholesale price that can be used as benchmarks by channel members in order to evaluate if the incentives should be implemented or not. I illustrate our results with numerical simulations indicating the channel‐coordinating wholesale price values where we observe an increase in both channel members' individual profits when the incentives are implemented (i.e., with respect to the status quo). These results can be explained by the decrease in retail price and the increase in local and national advertising. Both effects explain the increase in brand goodwill and demand when the incentives are implemented. [ABSTRACT FROM AUTHOR]