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In insurance, proposing an accurate premium that is adjusted to the insured risk profile allows companies to better manage their portfolios and to be more competitive. Machine learning methods have recently been adopted for various improvements in insurance ratemaking, especially in the automobile industry. These models are specifically used to mine potential data information and to build a predictive model for a variable of interest using explanatory variables. In this paper, we aim to provide a pricing method for ratemaking individual healthcare insurance contracts using machine learning algorithms that are applied to a Tunisian healthcare insurance portfolio. We start with a simple Classification and Regression Tree, and we work toward more advanced methods that are Random Forest, Extreme gradient boosting, Support Vector Regression, and Artificial Neural network regression model. The predictive performance of these non-parametric methods is compared with the standard generalized linear model. Our results showed the applicability of machine learning in the healthcare insurance market and that the XGBoost algorithm outperforms the predictive capacity of the classical generalized linear model. [ABSTRACT FROM AUTHOR]

We develop an algorithm for solving a large class of nonlinear high-dimensional continuous-time models in finance. We approximate value and policy functions using deep learning and show that a combination of automatic differentiation and Ito's lemma allows for the computation of exact expectations, resulting in a negligible computational cost that is independent of the number of state variables. We illustrate the applicability of our method to problems in asset pricing, corporate finance, and portfolio choice and show that the ability to solve high-dimensional problems allows us to derive new economic insights. [ABSTRACT FROM AUTHOR]

With the rise of social media and the peer-to-peer economy, sellers can easily tell potential buyers about themselves and their process of producing products and services. This research investigates the influence of a central aspect of the production process that sellers can communicate—their production enjoyment. Buyers are willing to pay a higher price, are more likely to click on ads, and are more likely to choose a product or service when the seller signals that they enjoy producing it. In contrast, sellers are willing to accept lower prices, and actually charge less, for products and services they enjoy producing. Both buyers and sellers make the inference that production enjoyment leads to higher quality products/services, but only buyers rely on this inference when forming their pricing judgments relative to sellers. Nine studies illustrate these effects across a wide variety of products and services, participant samples, and operationalizations of production enjoyment. They show that signals of production enjoyment can influence buyers more than other established signals (e.g., effort) and demonstrate contexts where these effects are more and less likely to occur. These findings offer practical recommendations for both buyers and sellers as well as a variety of theoretical contributions. [ABSTRACT FROM AUTHOR]

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]

This paper examines sharing platform in the agricultural supply chain that serves as a direct link between farmers and consumers. We analyze the competition between the sharing platform and the retailer when they face two types of consumers (switchers and retailer-loyal consumers) based on whether they are loyal to the retailer. We investigate how the number of switchers and farmers' marginal costs affect the retailer's optimal pricing and profit. We first analyze the case of the sharing platform being a non-profit organization, where farmers pay no fee to use the platform. Our analysis reveals several interesting findings. First, the presence of the non-profit sharing platform will induce the retailer to reduce its equilibrium retail price, making it worse off; both consumers and farmers will become better off. Second, with more switchers in the market, the retailer will decrease its equilibrium retail price; the platform's equilibrium market-clearing price may increase or decrease. Moreover, farmers' marginal costs for high-type products have nonmonotonic effects on the firms' equilibrium prices. In an extension, we consider a for-profit platform, who charges farmers a percentage fee for sales. We find that a higher percentage fee by the for-profit sharing platform may reduce its profit. [ABSTRACT FROM AUTHOR]

Software firms are increasingly adopting an open source strategy, allowing them to leverage the effort exerted by the open source community toward improving software quality. In addition to embracing a proprietary or fully open source strategy, several firms choose a partial openness strategy wherein only certain parts of the code are open source while the rest is proprietary. Specifically, when adopting a partial openness strategy, a firm may choose to make the core software code open source while keeping the extension software code proprietary or keep the core proprietary and make the extension open source. When making decisions related to different openness strategies, firms need to take into account the level of effort they are exerting toward the improvement of the quality of software, the level of engagement of the open source community, and pricing. Hence, the decisions related to a firm's openness strategy are not straightforward. While this is an important question for many firms, it has not been analyzed in the literature. In this research, we attempt to fill this important gap by analyzing different openness strategies in the context of resource allocation for fixing defects. Specifically, using a game-theoretic model, we explore when a firm should make its software fully open source or partially open source and when it should keep it proprietary. Our results show that when the baseline demand for the firm increases with the extent of openness, the firm should either make its software fully open or keep it proprietary and, importantly, should not rely on partial openness. Next, in scenarios where customers are highly sensitive to security risks, the demand loss to efficiency gain ratio has an important role in determining a firm's optimal openness strategies. These findings provide important insights to firms on how to effectively plan their openness strategies and also establish a basis for future research on the topic of partial openness. [ABSTRACT FROM AUTHOR]

Over the last half-century, consumer research has often depicted scarcity as a dominant factor increasing price. But should we assume that scarcity's upward pressure on price remains intact, in a world where novel forms of digital products proliferate? In this article, we propose that blockchain-encrypted digital goods, in particular, non-fungible tokens (NFTs), offer good reason to revisit this assumption. In this context, we argue and find that social value can outweigh intrinsic value as a determinant of willingness-to-pay. As a result, when scarcity threatens access to high levels of social value, its effect on price can be negative rather than positive—an inversion of a pattern typically observed for offline collectibles. Secondary data taken from the NFT platform Opensea and a set of experimental studies support this social value-based lens. Given these findings, we propose a research agenda to ground future work in this area. We also suggest that NFTs offer a laboratory in which past theories related to social value, scarcity, and price can be reconsidered and future theories developed, hopefully allowing consumer researchers to lead knowledge development in these domains over the next 50 years. [ABSTRACT FROM AUTHOR]

We present a method for determining whether errors in expectations explain asset pricing puzzles without imposing assumptions about the error mechanism. Using accounting identities and survey forecasts, we find that errors in expected long-term inflation explain price variation, return predictability, and the rejection of the expectations hypothesis for aggregate stock and bond markets. Errors in short-term (long-term) nominal earnings growth expectations explain (do not explain) stock price variation and return predictability. The relevant errors are consistent with mistakes about the persistence of forecasted variables and the response to surprises. A simple framework based on fundamental extrapolation successfully replicates these findings. (JEL G40, G12, G14, E71) [ABSTRACT FROM AUTHOR]

This article is the first generalizable empirical analysis of dual branding, that is, the supply of private labels (PLs) by national brand (NB) manufacturers. The authors compile a unique data set combining the identity of PL suppliers in over 260 packaged goods categories with multiple years of scanner data in the Spanish grocery market to offer several contributions. First, they provide new descriptive insights on the prevalence of dual branding in categories where the manufacturer does and does not have NBs, the longevity of PL supply arrangements, and the differences in PL sourcing across retailers. Second, they integrate the literature on motivators and dissuaders of dual branding and test the impact of relevant manufacturer, retailer, and dyad characteristics on PL supply in NB and non-NB categories. The results reveal a more nuanced empirical reality than is evident from prior research regarding the role of multicategory scope, fighter brands, NB differentiation, and size and positioning of the retailer's PL. Third, they examine the outcomes of PL supply for the NBs of dual branders and find that starting (terminating) PL supply to a retailer significantly benefits (hurts) the relative distribution depth but not the relative share of the dual brander's NBs at that retailer. [ABSTRACT FROM AUTHOR]

Combining experimental data sets from seven individual studies, including 255 asset markets with 2,031 participants, and 36,326 short-term price forecasts, we analyze the role of heterogeneity of beliefs in the organization of trading behavior by reproducing and reconsidering earlier experimental findings. Our results confirm prior evidence that price expectations affect trading behavior. However, heterogeneity in beliefs does not seem to drive overpricing and asset market bubbles, as suggested by earlier studies, and we find no indication of short-term beliefs being better determinants of trading behavior than longer-term beliefs. [ABSTRACT FROM AUTHOR]

Price reductions take either an integrated form (e.g. a discount shown directly on the price tag) or a non-integrated form (e.g. a discount contained in a coupon sent to consumers and thus separate from the price tag). This research examines how non-integrated versus integrated promotions influence choices among vertically differentiated products. Under an integrated promotion (e.g. $10 off) applicable to multiple products (e.g. original list prices: $50 vs. $30), consumers directly compare these products' post-promotion final prices displayed on their price tags (after a reduction of $10: $40 vs. $20). In contrast, under a non-integrated promotion of the same monetary value, consumers simply compare these products' original list prices ($50 vs. $30) and neglect their post-promotion final prices, which require calculations. The list prices ($50 vs. $30; relative to the final prices: $40 vs. $20) as a basis for price comparison reduce the perceived price difference between these products. Consequently, a non-integrated promotion (compared to an integrated promotion) increases consumers' choice of higher-priced products. A series of experiments (N  = 5,187) demonstrate this effect and support the final price neglect mechanism. Furthermore, although attenuated, this effect still emerges for price reductions of a smaller magnitude or in a percent-off format. [ABSTRACT FROM AUTHOR]

Business models play a key role in companies' profit growth and competitiveness. A growing number of companies not only sell products but also provide leasing services. In traditional leasing models, companies usually charge customers for the time they occupy the product, but ignore differences in how long and how often customers actually use the product. In practice, customers have different product usage patterns, which will affect their purchase choice. Considering the pooling effect in the leasing service network, this paper describes customers' usage patterns in two dimensions (product occupancy time and utilisation rate) and determines the optimal pricing under three models (selling, leasing, and their hybrid model) to maximise corporate profits. Through comparative analysis, the optimal business model selection decision is obtained, and its market performance is also analysed. The results show that when the leasing service operational capability is strong, the pure leasing service model is superior; otherwise, the result also depends on the product value creation capability. When this capability is high, the hybrid model will be selected; otherwise, the pure selling model will be better. This result differs from the generally held result in previous studies that the hybrid model is more profitable in most cases. [ABSTRACT FROM AUTHOR]

We examine the association between margin requirements and the market's efficiency in incorporating firm-specific and market-level public news. Combining the Fed's 22 changes in margin requirements with a hand-collected sample of earnings announcements between 1934 and 1975, we show that higher margin requirements induce greater delay in incorporating earnings information into prices. We draw similar conclusions when we analyze the Hou and Moskowitz (2005) price delay measure, as well as indirect measures of leverage constraints over recent years. Further tests suggest that, despite the Fed's expressed intent to curtail excess speculation, higher margin requirements restrict trading by arbitrageurs more than noise traders. [ABSTRACT FROM AUTHOR]

Momentum profits depend mainly on the short leg and therefore on barriers to short sales. Our research indicates that the decline in momentum profitability in the past 2 decades is driven partly by a contemporaneous growth in stock options trading. Stock options offer an alternative to short selling, augmenting the stock lending market, and thereby contributing to improved pricing efficiency. The resulting reduction in barriers to short sales contributes to lower returns to momentum trading from the short leg. Our results persist after matching stocks with and without options based on different firm-level characteristics. [ABSTRACT FROM AUTHOR]

Retailer price promotions, and in particular multi-unit deals such as the ubiquitous "buy one, get one," are often criticized as a cause of food waste, presumably because they lure households into buying more than they can realistically consume. In this research, the authors combine field data and experiments to provide the first systematic test of this claim. The field data, which span eight frequently purchased perishable foods, show no evidence of a positive relationship between single-unit or multi-unit price promotions and food waste. In fact, households that took advantage of a multi-unit deal reported wasting less than did households paying regular prices (RPs), but only when the quantity purchased was larger than usual. Given this result, and that households also reported consuming and freezing more, the authors hypothesize that promotion-induced overbuying triggers a concern for food waste that encourages waste prevention. One experiment finds support for this mechanism. A second experiment shows that the effect on food waste concerns is moderated by perishability and versatility but unaffected by convenience and healthiness. Overall, then, this research invites regulators and other professionals to rethink their stance on price promotions and work with retailers to design smart campaigns that motivate waste awareness and management. [ABSTRACT FROM AUTHOR]

Publishers face an existential threat from a variety of news aggregators, such as free aggregators (e.g., Google News, Yahoo News), micropayment-facilitating aggregators (e.g., Blendle), and subscription-charging aggregators (e.g., Apple News+). The authors seek to theoretically examine whether publishers can collaborate and compete with the different types of news aggregators and, if so, what pricing and content-sharing strategies publishers should pursue. In the absence of a news aggregator, publishers sell their content as a composite publication; this intensifies interpublisher price competition and hurts publishers' profits. A free aggregator, however, could help unbundle the articles of a publisher. Moreover, if publishers share articles on the same topic with a free aggregator, they can completely eliminate interpublisher competition and replace it with competition between the aggregator and the publishers, but they only partially eliminate interpublisher competition if they share articles on different topics with it. Yet, the free aggregator needs to bring sufficient additional traffic to the publishers to motivate them to share content and collaborate with it. Conversely, publishers will be willing to collaborate with a micropayment-facilitating aggregator even if it does not bring additional traffic to the publishers. This is because a micropayment-facilitating aggregator helps publishers unbundle their content and price discriminate. Lastly, publishers can be motivated to collaborate even with a subscription-charging aggregator that is powerful enough to dictate the terms of the revenue-sharing arrangement with the publishers. This is because the subscription-charging aggregator improves its profits without hurting the publishers' surplus. [ABSTRACT FROM AUTHOR]

We estimate a narrative factor pricing model from news text of The Wall Street Journal. Our empirical method integrates topic modeling (LDA), latent factor analysis (IPCA), and variable selection (group lasso). Narrative factors achieve higher out-of-sample Sharpe ratios and smaller pricing errors than standard characteristic-based factor models and predict future investment opportunities in a manner consistent with the ICAPM. We derive an interpretation of the estimated risk factors from narratives in the underlying article text. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online [ABSTRACT FROM AUTHOR]

How synchronized are short sellers? We examine a unique data set on the distribution of profits across a stock's short sellers and find evidence of substantial dispersion in the initiation of their positions. Consistent with this dispersion reflecting "synchronization risk," that is, uncertainty among short sellers about when others will short sell, more dispersed short selling signals i) greater stock overpricing and ii) longer delays in overpricing correction. These effects are prevalent even among stocks facing low short-selling costs or other explicit constraints. Overall, our findings provide novel cross-sectional evidence of synchronization problems among short sellers and their pricing implications. [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 research investigates how a price promotion on a fast-moving consumer good influences the sales of substitute products in a retail shelf or online display. An analysis of supermarket yogurt data finds that when nonpromoted products are strong substitutes for the promoted product, a 1% decrease in the price of the promoted product results in a.25% decrease in the sales of proximal products but no change in the sales of distal products—a negative promotion-proximity effect. However, when nonpromoted products are weak substitutes for the promoted product, a 1% decrease in the price of the promoted product results in a.10% increase in the sales of proximal products but no change in sales for distal products—a positive promotion-proximity effect. Subsequent studies show that these effects occur because a proximal strong substitute is more likely to enter a consideration set with the promoted product (negative promotion-proximity effect) and a proximal weak substitute is more likely to be seen and considered by a consumer who is not interested in the promoted product (positive promotion-proximity effect). [ABSTRACT FROM AUTHOR]

Recent research has highlighted a difference in the way consumers approach choice sets. Some consumers focus on products' quality benefits (vertical differentiation): their selections are driven by the level of quality obtained relative to the price paid. Other consumers focus on products' taste benefits (horizontal differentiation): their selections are driven by acquiring personal tastes at favorable prices. This article aims to investigate how consumers' benefit focus, a continuum anchored by quality and taste, drives their preferences between retailers differing in pricing strategies. All else equal, consumers who focus on taste benefits will prefer EDLP stores (infrequent discounters), while consumers who focus on quality benefits will prefer Hi-Lo stores (frequent discounters). Findings from our experiments and an analysis of consumer panel data corroborate this relationship. This work also shows the mediating role of perceived value and the effect of several moderators: the strength of the price–quality relationship, the pattern of discounts, and cherry-picking costs. [ABSTRACT FROM AUTHOR]

Standard choice-based conjoint models often ignore or insufficiently approximate consumers' budget constraints, despite the prominent role of budget constraints in economic theory. The authors offer a theoretically motivated improvement to the choice-based conjoint model that is especially appropriate for high-ticket durable goods and develop a Bayesian method for the inference of unobserved budget constraints. The proposed method leverages respondents' stated budget constraints that suffer from measurement error and respondents' financial demographic variables as additional information to reduce the dependency on functional form assumptions in the estimation. The authors show that accounting for budget constraints substantially increases model fit and the accuracy of competitive pricing in an industry-grade discrete-choice experiment on consumer preferences for high-end laptops. The proposed model performs better than the canonical linear price benchmark model, which is not flexible enough to approximate budget constraints. In theory, more flexible utility specifications, such as the nonlinear dummy price model, can approximate consumers' budget constraints. However, they perform poorly when only finite data are available. The authors conclude that applied researchers in industry and academia will benefit from having a better tool for estimating budgets in high-ticket categories. [ABSTRACT FROM AUTHOR]

Many of the Federal Reserve's (the Fed's) monetary policy operations involve trading with primary dealers. We find that, for agency MBS, dealers charge 2.5 cents (per $100 face value) higher selling to the Fed than to non-Fed customers. Controlling for the same dealer, same security, and same trading time, this discriminatory pricing likely arises from dealers' market power rather than inventory costs. Further, matching trade size reduces the price differential by more than half, implying that dealers' market power greatly relates to the Fed's purchases in large amounts, whereas the Fed's limited breadth of counterparty choice also plays some role. [ABSTRACT FROM AUTHOR]

We consider a low-carbon tourism supply chain (LTSC) network composed of two low-carbon scenic spots (LSSs) and two travel agencies (TAs). The LSSs as leaders and the TAs as followers play Stackelberg games in the vertical direction. Meanwhile, the competing LSSs play Nash game to determine emission reduction efforts and ticket prices, and the competing TAs play Nash game to conduct retail prices. We establish four kinds of differential game models with different LTSC network structures, derive the equilibrium decision-makings of the LSSs and TAs, and explore the influences of competition or cooperation at vertical and horizontal level of the LTSC network members on the equilibrium solutions of the LSSs and TAs, low-carbon level of tourism products and performance of the LTSC network. Then, we find that the low-carbon preference of tourists improves the low-carbon level of tourism products, while the competition intensity between the LSSs leads to the decrease of the low-carbon level of tourism products. In addition, the results indicate that horizontal or vertical cooperations among the LTSC network members are not always conducive to the performance of the whole LTSC network. Only when the sensitivity of tourist demand to retail price meets certain conditions, these cooperations can develop tourism products with higher low-carbon level and bring higher revenues. [ABSTRACT FROM AUTHOR]

This article examines whether and how stock mispricing can affect the probability of CEO turnover. In a sample of 1,573 US public firms, I find that, after controlling for fundamental performance, a 1-standard-deviation negative uninformative stock price shock increases the likelihood of CEO turnover by 10%. The mispricing-turnover sensitivity is stronger at firms with an independent board, and a difference-in-difference analysis further supports that finding. Ancillary results suggest that independent directors' career concerns may play a role in the response of independent boards to mispricing. [ABSTRACT FROM AUTHOR]

This article constructs and examines enhanced global return factors. I focus on three different enhancement approaches. First, I incorporate information about the covariance structure in the cross-section of stock returns. Second, I employ volatility-reducing techniques in the time series. Third, I exploit diversification benefits. I form six categorical factors by aggregating information from 214 characteristics. Further, I diversify across factors. The enhancement mechanisms are largely successful and when jointly applied increase the optimal Sharpe ratio on average by a factor of 1.96 compared to the traditional factors. My results point to the importance of employing efficient factors in asset pricing studies. [ABSTRACT FROM AUTHOR]

Economically insignificant tick sizes encourage undercutting behavior, thus harming market quality. Theoretical work shows that increasing tick sizes in unconstrained markets reduces undercutting and improves market quality. Equity market pricing grids are generally too coarse to test this prediction. We examine a cryptocurrency market with infinitesimal tick sizes where undercutting limit orders acquire price priority without meaningful economic cost. We show that increasing tick sizes reduces undercutting behavior, increases liquidity provision and quoted depth, and reduces transaction costs for institutional and retail-sized trades while decreasing short-term volatility. Tiny tick sizes are suboptimal, supporting increased minimum trading increments in tick-unconstrained markets. [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]

The high cost of gluten‐free products (GFPs) is being discussed as a potential barrier to adherence to a gluten‐free diet, rendering monitoring of their pricing an ongoing demand in a market subject to continuous fluctuations. The current study aimed to assess the current pricing status of GFPs in the Greek retail market, with a focus on differences between staple and non‐staple foods. The retail price and packaging weight of all available GFPs and their gluten‐containing (GCPs) counterparts of a GFP‐shopping basket (formulated based on the results of a preceding online survey) were recorded by visiting one store of the five most popular reported supermarket chains. The food categories were grouped into staple (e.g. breads, pasta and flours) and non‐staple (e.g. chips, sweets and sauces) foods. Adjusting for supermarket chain and product type, a quantile mixed regression model was applied to assess the extent to which median product price (per 100 g) differed between GFPs and GCPs. The unique products recorded were 1058 (of which 408 GFPs), with a total of 2165 retail price recordings. While the overall median price/100 g of GFPs was not found to be significantly different from that of GCPs, the median price of staple GFPs was estimated to be higher than staple GCPs (+€1.03 [95% CI: €0.93; €1.13] per 100 g), whilst that of non‐staple GFPs was slightly lower (−€0.20 [95% CI: −€0.37; −€0.02] per 100 g). In conclusion, the persisting higher cost of staple GFPs suggests the need for ongoing financial support for people with coeliac disease. [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]

With the development of new technology for multiple energy applications, household appliances using electricity and other energy sources are becoming increasingly abundant. Users can freely choose the way of energy consumption based on the price of electricity and other energy sources. The phenomenon has become one of the important factors affecting real‐time pricing. This study considers real‐time pricing in the case of multiple energy coexistence on the user side. According to the spatiotemporal coupling of electricity and other energy sources and the relationship between other energy sources and total energy consumption, an optimization model that satisfies the actual situation is established. By using the relaxation theory and dual decomposition technology, a partially distributed algorithm is proposed for multi‐period coupling and finding the optimal energy scheduling scheme for the energy company and each user, so as to maximize social welfare. In addition, under the background of multiple energy coupling, real‐time pricing can guide users to adjust their electricity consumption behaviour vertically and horizontally, change the type of energy, meet energy demand for end users and effectively reduce the peak‐to‐average ratio. Simulation results verify the rationality of the model and the effectiveness of the algorithm. [ABSTRACT FROM AUTHOR]

Managed entry agreements and especially financial-based agreements are commonly used in European countries for innovative cancer pharmaceuticals. These agreements facilitate access to innovative treatments while mitigating financial risks for payers. This study focuses on the confidential price agreement made by the Dutch government for the reimbursement of pembrolizumab, the implications of broadening indications on cost-effectiveness, and the viability or desirability of said agreement. We selected 5 indications in which pembrolizumab was deemed effective and developed portioned survival models for each indication. Survival and progression-free survival data from the published trials were utilized to recreate individual patient data, and we extrapolated—using parametric models—to a time horizon of 30 years. Inputs for both quality of life and costs were derived from the available literature and were indexed. The incremental cost-effectiveness ratios ranged between €35 313 and €322 349 per quality-adjusted life-year, depending on the indication. Only 1 indication fell under the €80 000 (or €100 000) cost-effectiveness threshold. When applying the average reported discount on intramural pharmaceuticals in The Netherlands, incremental cost-effectiveness ratios ranged between €20 881 and €252 934 per quality-adjusted life-year gained, and the €80 000 (or €100 000) threshold was met in 3 indications out of 5. Our results show that pembrolizumab could be cost-effective in some indications, depending on the confidential price agreement established. However, the possibility of reimbursing not cost-effective care when the price is anchored in 1 indication remains possible. Indication-based pricing could help align value and price for innovative pharmaceuticals that are subject to indication broadening. • Market entry agreements are broadly use in the European Union and especially financial-based agreements are utilized to mitigate financial risks associated with reimbursement of innovative pharmaceuticals. • How market agreements are performing can be difficult to assess because these agreements are partly covered in secrecy. • Our results showed that, without discount, 4 of 5 indications selected for pembrolizumab would not meet cost-effectiveness thresholds. Therefore, they demonstrate the potential risks for both payers and pharmaceutical companies when engaging in market entry agreements, especially in financial-based agreements for products subject to indication expansion. [ABSTRACT FROM AUTHOR]

Using a novel combination of mortgage datasets, we analyze the effects of two policy levers influencing the scope of Fannie Mae and Freddie Mac's (Government-Sponsored Enterprises, GSEs) involvement in the U.S. residential mortgage market. First, we find that small changes in mortgage guarantee fees charged by the GSEs were essentially fully passed through to consumers, with limited effects on mortgage demand. This implies that small fee changes are primarily transfers between mortgage consumers and taxpayers while the GSEs remain in federal conservatorship. Second, the data suggest that marginally lowering maximum conforming loan size limits would cause most affected consumers to reduce their loan amounts to the new maximum. Our findings provide new detailed evidence on how GSE policy shapes mortgage availability and contrast the differing effects on consumers of two potential policy levers to reduce (or increase) the scope of GSE lending. Additional survey data indicate that borrowers' shopping behavior and incomplete information may also influence the effects of GSE policy changes. [ABSTRACT FROM AUTHOR]

In order to improve the profitability and customer service management of original equipment manufacturers (OEMs) in a market where full-service (FS) and on-call service (OS) co-exist, this article extends the optimising modelling for pricing FS repair contracts with the effects of dynamic learning and forgetting. Along with considering autonomous learning in maintenance practice, this study also analyses how induced learning and forgetting process in a workplace put impact on the pricing optimising model of FS contracts in the portfolio of FS and OS. A numerical analysis based on real data from a medical industry proves that the enhanced FS pricing model discussed here has two main advantages: (1) It could prominently improve repair efficiency, and (2) It help OEMs gain better profits compared to the original FS model and the sole OS maintenance. Sensitivity analysis shows that if internal failure rate increases, the optimised FS price rises gradually until reaching the maximum value, and profitability to the OEM increases overall; if frequency of induced learning goes up, the optimal FS price rises after a short-term downward trend, with a stable profitability to the OEM. [ABSTRACT FROM AUTHOR]

This paper considers optimal pricing in a system with limited substitutable resources, such as certain goods or services. Prices for the different resources have to be set and then customers with heterogeneous preferences show up sequentially. Customers, of n types, select an item from the m available resources, depending on their valuations of the resources and the prices. The goal is to analyze this optimization problem, characterize a set of candidates to optimal solutions and provide methods for solving it. We prove that this problem is NP-hard to approximate within a factor O (n 1 - ε) for any fixed ε > 0 . Another important contribution is to prove that, the space of prices (which in principle is a continuous domain in R m ), can be reduced to a finite set of vectors of cardinality m m - 2 n m 2 m . For a deterministic version of the problem, where the customer types are known to the firm, we provide a mathematical program that chooses the best set of prices. We report extensive computational results showing the usefulness of our exact approach to solve medium size problems with up to 200 customers and different assortments of products and customer types. We then show how to approximate the stochastic model by a small number of solutions of deterministic scenarios solved using a mixed-integer linear program. [ABSTRACT FROM AUTHOR]

This study proposes a framework of an urban passenger-and-package sharing (PPS) system that utilizes e-hailing taxis to transport packages in addition to passengers. We examine the interactions between stakeholders and highlight the role of the pricing strategy in the system, including passenger fare discounts and driver incentives for PPS trips. Higher discounts and incentives stimulate more passengers and taxi drivers, respectively, to participate in the PPS system but possibly limit the profit of the service provider. A multi-agent simulation model is developed to analyze the influences of the pricing strategy on the behaviors of the service provider, passengers, and taxi drivers. The real-world case study demonstrates that the service provider, passengers, and taxi drivers benefit from different combinations of the passenger fare discounts and driver incentives. The pricing strategy could be set up to produce the system optimal (SO) situation that maximizes the total benefit, or win-win situations that simultaneously benefit all stakeholders—the service provider gains a higher profit, passengers enjoy lower travel costs, and taxi drivers have higher incomes when compared to the traditional e-hailing taxi system. The public authority is suggested to provide a subsidy to expand the domain of win-win situations to cover the SO situation, such that the system benefits all stakeholders and obtains the maximum total benefit. • Envisions a multi-stakeholder framework for PPS system based on e-hailing taxis. • Pricing concerns passenger fare discount and driver incentive for PPS service. • Analyzes the impact of pricing on system profit, passenger cost and driver income. • Optimal pricing maximizes the total benefit but may distract some stakeholders. • Evaluates the effectiveness of subsidy in coordinating win-win and SO situations. [ABSTRACT FROM AUTHOR]

Several factors affect customers' decisions regarding service selection. Two of the essential factors are the price and the service quality. The seller's credibility is also among the influential factors in selecting a service that is reinforced by advertising. The emergence of the Internet has led to increasing attention by sellers to advertising through online group buying (OGB) platforms. Sellers aim to attract new customers by offering discounts on OGB platforms. In this paper, the seller can sell its service through offline and online channels during two current and future courses. The aim is to determine the optimal strategy for the seller when deciding to join the OGB platform. All parameters of the problem are determined as fuzzy variables. Accordingly, this paper develops a fuzzy mathematical model to simultaneously determine price, service quality, and advertising level in a dual channel supply chain. A cooperative game between the seller and the OGB platform is developed under different refunding and revenue sharing scenarios for the centralized model. The optimal solutions of the problem are then defined using the game and fuzzy sets theories for each scenario. A numerical example is presented to indicate the effectiveness of the theoretical results of the models and developing management insights. In addition, sensitivity analyses also provide the effect of changes in essential parameters on the seller's decisions. [ABSTRACT FROM AUTHOR]

Word of mouth (WOM) is crucial in customers' purchasing decisions and affects companies' long-term profits. This study examines the long-term trends in companies' dynamic pricing and profits by using the Hamiltonian function method and dynamic simulation to construct a dynamic equation. It takes into account the intensity of word of mouth faced by companies and analyzes the level of publicity and consumers' predictions of product quality. In this paper, we also discuss the interactive processes between WOM and advertising levels, the two most prominent market factors, and their ultimate impact on companies. The experimental results show that elevated levels of external advertising can potentially prompt companies to establish higher product pricing strategies, particularly in scenarios where the intensity of word of mouth is pronounced. In the initial phases of market development, the saturation level of consumers within the market exerts a negligible influence on companies' long-term profit margins. Conversely, the rate of natural attrition from consumers' upper threshold of product quality expectations distinctly impacts companies' profitability. [ABSTRACT FROM AUTHOR]

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Offering Maintenance Service Contracts (MSCs) for production equipment can be a good source of revenue for the Providers of these services. To do this, designing an optimal MSC with a minimum price will be of great interest to service providers. In this paper, the effect of conducting periodic preventive maintenance on the failure process of a given equipment item and its corresponding cost are studied. Assuming minimal repair at failure with a random repair cost, the expected cost of maintenance service is estimated. Due to the time delay between selling the contract and paying the repair bills, the time value of service cost at the time of selling the contract is derived. Then, the cost-plus approach is used to determine the price of the MSC. In the presented model, the service provider determines the number of preventive maintenance and the improvement level to minimize the expected price of the MSC. A numerical example with comprehensive sensitivity analysis is presented to illustrate the model and its parameters' effect. The result shows that the presented model helps the service provider to design an MSC with a minimum price while assuring the profit margin. [ABSTRACT FROM AUTHOR]

In this paper, we explore dynamic market share and public healthcare costs of trastuzumab's evergreening (subcutaneous) variant during introduction of trastuzumab's competitive biosimilar variants in the Netherlands. We used a time series design to assess dynamic market share of trastuzumab's evergreening variant after introducing trastuzumab's biosimilar variants, focusing on the number of treatments and patients. The public healthcare costs of this evergreening strategy were estimated using administrative claims data. Our results show that the original trastuzumab was completely replaced by the subcutaneous and biosimilar variants. The uptake of the subcutaneous form peaked at 50% market share but after the introduction of biosimilars progressively reduced to a market share of 20%, resulting in a more competitive market structure. The public healthcare costs for trastuzumab significantly decreased after the introduction of the biosimilars. After the introduction of the biosimilars, a substantial price drop is visible, with the subcutaneous version, still under patent, also falling sharply in price but less strongly than the iv/biosimilar version. As the costs are publicly funded, we recommend a more explicit societal debate to consider if the potential benefits of subcutaneous Herceptin® (and other similar medicines) are worth the additional costs, and at which price it should be reimbursed as the part of the benefit package. [ABSTRACT FROM AUTHOR]

This study investigates the pricing strategies of a mobile payment platform connecting merchants and customers who may bypass the platform and trade in cash. Our analytical model incorporates cross-side network externalities at both sides of the platform. We find that the optimal pricing strategy involves cross-subsidization, including subsidizing customers to register for the service while charging the merchants per transaction. Moreover, the technology option adopted by the platform influences this optimal pricing format. In particular, the platform should subsidize customers more if the payment technology imposes larger transaction costs on customers and charge merchants more if banks demand a higher payment processing fee. Our major findings remain qualitatively valid when per-transaction subsidy is available and the marginal benefit of cross-side network externalities diminishes. Finally, the presence of a platform improves social welfare if the per-transaction subsidy sufficiently stimulates consumption on the platform. [ABSTRACT FROM AUTHOR]

Introduction: Innovative pricing and payment/reimbursement schemes have been proposed as one part of the solution to the problem of patient access to new health technologies or to the uncertainty about their long-term effectiveness. As part of a Horizon Europe research project on health innovation next generation pricing and payment models (HI-PRIX), this protocol illustrates the conceptual and methodological steps related to a scoping review aiming at investigating nature and scope of pricing and payment/reimbursement schemes applied to, or proposed for, existing or new health technologies. Methods: A scoping review of literature will be performed according to the PRISMA guidelines for scoping reviews (PRISMA-ScR) guidelines. The search will be conducted in three scientific databases (i.e., PubMed, Web of Science, and Scopus), over a 2010–2023 timeframe. The search strategy is structured around two blocks of keywords, namely "pricing and payment/reimbursement schemes," and "innovativeness" (of the scheme type or scheme use). A simplified search will be replicated in the gray literature. Studies illustrating pricing and payment/reimbursement schemes with a sufficient level of details to explain their characteristics and functioning will be deemed eligible to be considered for data synthesis. Pricing and payment/reimbursement schemes will be classified according to several criteria, such as their purpose, nature, governance, data collection needs, and foreseen distribution of risk. The results will populate a publicly available online tool, the Pay-for-Innovation Observatory. Discussion: The findings of this review have the potential to offer a comprehensive toolkit with a variety of pricing and payment schemes to policymakers and manufacturers facing reimbursement and access decisions. [ABSTRACT FROM AUTHOR]

Purpose. The purpose of this research is to propose a tool for designing a microcredit risk pricing strategy for borrowers of microfinance institutions (MFIs). Design/methodology/approach. Considering the specific characteristics of microcredit borrowers, we first estimate and measure microcredit risk through the default probability, applying a parametric technique such as logistic regression and a non-parametric technique based on an artificial neural network, looking for the model with the highest predictive power. Secondly, based on the Basel III internal ratings-based (IRB) approach, we use the credit risk measurement for each borrower to design a pricing model that sets microcredit interest rates according to default risk. Findings. The paper demonstrates that the probability of default for each borrower is more accurately adjusted using the artificial neural network. Furthermore, our results suggest that, given a profitability target for the MFI, the microcredit interest rate for clients with a lower level of credit risk should be lower than a standard, fixed rate to achieve the profitability target. Practical implications. This tool allows us, on the one hand, to measure and assess credit risk and minimize default losses in MFIs and, secondly, to promote their competitiveness by reducing interest rates, capital requirements, and credit losses, favoring the financial self-sustainability of these institutions. Social implications. Our findings have the potential to make microfinance institutions fairer and more equitable in their lending practices by providing microcredit with risk-adjusted pricing. Furthermore, our findings can contribute to the design of government policies aimed at promoting the financial and social inclusion of vulnerable people. Originality. The personal characteristics of microcredit clients, mainly reputation and moral solvency, are crucial to the default behavior of microfinance borrowers. These factors should have an impact on the pricing of microcredit. [ABSTRACT FROM AUTHOR]

The goal of this study is to develop a social pricing model for the consumption of a good such drinking water in order to finally uphold the ideal of consumer equality. A deficit results from the first-tier monopoly's price; furthermore, second-class pricing may have detrimental effects on fairness. The concern for equity does, in fact, necessitate the inclusion of social value in the price model. The empirical research demonstrates that the Greater Tunis region's households face an appreciation for the physical quality of this good when consuming drinking water, Social pricing is therefore primarily based on a customer's willingness to pay (WTP) in accordance with their preferences. [ABSTRACT FROM AUTHOR]

Problem definition: We investigate how the characteristics of consumers and a service firm influence the firm's optimal pricing and promised delivery-time decisions as well as the optimal investment in the quality of delivery reliability information available to consumers. Methodology/results: We use utility, queuing, and choice modeling theories to model consumers' behavior and to find solutions to the firm's profit maximization problem. Managerial implications: The optimal strategy is to disclose either error-free delivery reliability information or no information at all. We also delineate conditions for each of the two strategies to dominate. Funding: This research was supported by the General Research Fund (GRF) of the Hong Kong Research Grants Council under Research Project LU13500822. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2023.0223. [ABSTRACT FROM AUTHOR]

Problem definition: Leading specialty coffee roasters rely on direct trade to source premium coffee beans. We examine a roaster who sells two basic types of roasts: (1) a single-origin roast sourced from a specific locale and (2) a blend roast that uses a mix of beans from sources that vary over the course of a year. The prices of blend roasts are lower than those of single-origin roasts and appeal to a larger market. We study how characteristics of the operating and market environment affect the optimal sourcing strategy for single-origin beans. Methodology/results: We develop a two-stage stochastic program with recourse that reflects these characteristics. A roaster has the option to allocate some of the single-origin beans for sale under a blend label, known as downward substitution. We identify three distinct optimal sourcing strategies—specialized (no downward substitution), diversified (consistent downward substitution), and mixed (between these extremes)—and show that they are robust under different definitions of yield and demand. Managerial implications: We identify four main insights: (1) Two factors determine which strategy is optimal: the mean price of the inferior product (blend label) and the marginal cost of the superior product (single-origin label). (2) When compared with the newsvendor model, we find distinct structural differences across strategies. For example, whereas the effects of increasing uncertainty on optimal quantity align with the newsvendor model under a mixed strategy, the effects are distinctly different under specialized and diversified strategies (e.g., monotonic decreasing behavior for specialized, no change in quantity under diversified). (3) The weighted average price of an agricultural product is decreasing in negative yield–price correlation. We coin this as the "farmer's curse," which carries lessons for direct trade sourcing (e.g., advocating against paying the grower at postharvest market prices). (4) We find evidence of a virtuous feedback loop wherein the grower–roaster relationship becomes stronger over time. Our findings also point to a simple signal that policymakers may use to identify coffee growing locales where targeted interventions can improve grower welfare. Funding: B. Kazaz is thankful for summer support provided by the Whitman School of Management, Syracuse University. Supplemental Material: The online appendix is available at https://doi.org/10.1287/msom.2021.0586. [ABSTRACT FROM AUTHOR]