Alternative Pricing Research Articles

An algorithm of selecting the pricing model for a construction contract

An algorithm has been developed for selecting a price model for a construction contract. This is important because price is one of the key parameters of a contract. It is this parameter that determines how much of the value created in the framework of the contract in a monetary form goes to the contractor and what remains to the client. The study has found that the contract drivers of pricing are the initial price, control, incentives (moral hazard), and the final price. This interpretation coincides with the fundamentals of contract theory and is a prerequisite for the fundamental credibility of the developed system. The basic input components of the decision-making algorithm on the most appropriate pricing strategy are the matrix of properties of contract price models and a metric of questions for evaluating the client’s respective priorities for the project. The system helps choose one of five key pricing strategies: CRC, MC, TC, LS or GMP, which are used in international practice. Applying the system of choosing the pricing model of a contract in conjunction with the system of selecting the organizational profile of the project provides an opportunity to choose the most appropriate strategy from 130 paired alternatives. The proposed approach in a cumulative way contributes to the success of construction projects and has a unified character. The formalized toolkit for benchmarking alternatives is the digital content of the strategic COMP – Contract Organizational Mechanisms: Pricing. The algorithm is built on estimating the priority vectors of pricing factors for a project (based on certain sets of ranks and ratings) with a further grading of the feasibility of using each of the alternative price models in the project. Approbation of the COMP system in the construction project of the Ice Arena in Kyiv has shown that the created conceptual model (the proposed algorithm) makes it possible to take an expedient decision on the pricing strategy for a contract with mathematical, high theoretical and practical argumentation

Returns from pulses in different regions of rajasthan at alternative price scenarios

Rajasthan is a major producer of pulses along with Madhya Pradesh, Maharashtra, Karnataka and Uttar Pradesh. In 2013-14 Rajasthan had total area of 4197.7 thousand hectares under pulses with production of 2490.9 thousand tones and productivity of 593 kgs/ha. Moong and moth in kharif season and gram in rabi season are grown extensively in Rajasthan. The study is primarily based on plot-level data collected from the 600 representative households of 60 tehsils for block period (2008-09 to 2010-11) for Rajasthan under CCS scheme of Directorate of Economics and Statistics, Ministry of Agriculture, Govt. of India, New Delhi. The study examined the nutrient consumption level, nutrient and irrigation subsidies availed by the pulses per hectare. The net returns of various pulses to the farmer, to the society and to the environment were estimated across zones. Pea, arhar, lentil and black gram were the pulses providing highest net return to the farmer at market price. After deducting the cost of subsidies which is a cost to the society, moong and gram in arid and semiarid zones and pea and arhar in central and south eastern humid zones gave highest net return at economic price. The estimated results for technical, allocative and cost efficiency indicated that the farmers were not operating at optimal scale and there is large scope for increasing output through factors which are under control of farmers. Lentil and arhar were most technical and cost efficient pulse crops while moong is the least technical and cost efficient pulse. In most of the pulses, on an average, the overwhelming cause of inefficiency is technical rather than allocative.

Asset Pricing Test Using Alternative Sets of Portfolios: Evidence from India

Empirical test of asset-pricing models are typically performed on portfolios based on firm-characteristics such as size and book-to-market ratios etc. However, because of their strong factor structure, the characteristic sorted portfolios do not provide a sufficient test for asset pricing models. In recent, the appropriateness to use characteristics sorted portfolios has been debated. Literature suggests various alternative test portfolios sorted by other attributes to improve the empirical tests. To address this issue, we construct three sets of test portfolios sorted by firm beta, volatility, and clustering method to test various asset pricing models. We examine whether portfolios sorted by the above methods can improve the explanatory power of various alternative asset pricing models. Our test results suggest that for unconditional models, the statistical significance and estimated risk premiums depend on the choice of tests portfolios. The conditional model has more power to explain the variation of average returns than the unconditional model.

Battles over numbers: the case of the Argentine consumer price index (2007–2015)

An unprecedented crisis of confidence in Argentina's public statistics rendered the declaration of a ‘National Statistical Emergency’ in 2016. This paper examines the battle over the Argentine consumer price index (CPI) between 2007 and 2015. It argues that in this dispute the index became the object of political struggle rather than a methodological controversy. The main characteristics of the Argentine CPI, its trajectory and the country’s inflationary history influenced the type of debate and the dispute that was possible and feasible. The battle was linked to the erosion of confidence in and social support for official statistics and to the emergence of alternative price indices. Both processes seriously undermined the government's ability to control inflation.

An empirical model of the decision to switch between electricity price contracts

ABSTRACTIn this paper, we explore how sensitive the timing of switches between electricity contracts is to current and past prices. We present a model for time series of individual binary decisions which depends on the history of past and present prices. The model is based on the Bayesian learning procedure which is at the core of sequential decision-making. Given a-priori distributions of the information conditional on the state of the world, we show that the model captures dependence on past prices in a straightforward fashion. We estimate by maximum likelihood the parameters of the model on a sample of Swedish households who decide over time between competing electricity price contracts. The estimated parameters suggest that households do respond to prices by switching between contracts and that the response to price can be sizeable for alternative price processes. Importantly, the model structure implies that in general, the response to a price change will not be immediate but delayed.

Swing Pricing and Fragility in Open-End Mutual Funds

How to prevent runs on open-end mutual funds? In recent years, markets have observed an innovation that changed the way open-end funds are priced. Alternative pricing rules (known as swing pricing) adjust funds’ net asset values to pass on funds’ trading costs to transacting shareholders. Using unique data on investor transactions in U.K. corporate bond funds, we show that swing pricing eliminates the first-mover advantage arising from the traditional pricing rule and significantly reduces redemptions during stress periods. The positive impact of alternative pricing rules on fund flows reverses in calm periods when costs associated with higher tracking error dominate the pricing effect.

Quality Management of Transport Services for Cargo Owners

The article addresses the concept of transport service quality as an essential tool for improving customer focus and the efficiency of rail transport in the implementation of cargo traffic. Issues have been investigated on current reforms going on in the railway transport market with regard to transport service. Valid procedures (both foreign and Russian ones) have been studied on freight owners’ evaluating transport service quality including All-Russian Project “Quality Index”. By this method, dynamics of change has been assessed in the fulfillment of basic indices of transport service quality, and causes of their inadequacy to ideal fulfillment have been described. Presented is the transport service quality management system for freight owners. The system is based on combination of natural assessment methods, optimization of quality level and assessment of efficiency of measures to increase the quality level. Based on logics of assuring transport service quality, a sequence has been proposed to analyze the transport quality indices systems: “quality of technical means → quality of operational work → quality of transport service”. Moreover, the quality of a subsequent system is the most objective characteristics of the previous system (systems) quality. It has been concluded that one of the major priorities in development of railway transport is to assure high-level quality of transport service. In addition to the most complete satisfaction of clients with railway transport services, the service quality makes it possible to increase attractiveness of railway companies in the transportation field and is the most important factor of competitiveness and the most promising for development as compared with alternative price factors.

Financial Impact of Alternative Pricing Benchmarks for Physician-Dispensed Drugs in the California Workers’ Compensation System

Pricing drugs in the California Workers' Compensation System (CAWCS) has become more difficult as there are increasingly fewer drugs listed in the Medi-Cal primary fee schedule, which is used as the source for CAWCS drug prices. This presents a challenge of providing timely and accurate CAWCS reimbursement. The objectives of this study are (1) to explore any trends in physician-dispensed drug prices; (2) to compare the proportion of drugs with and without a price and to determine the financial implications of repricing CAWCS physician-dispensed drugs with five alternative pricing benchmarks; and (3) to offer recommendations for the pricing benchmark to maximize pricing coverage and to remain budget neutral. We evaluated physician-dispensed drugs at the transaction level, reimbursed in the CAWCS. Frequency, reimbursement rate, and total and average paid costs were reported. We matched each claim line in the CAWCS to the corresponding unit price of an alternative price benchmark including average wholesale price, wholesale acquisition cost, direct prices, national average drug acquisition cost, and Federal Upper Limit. Average wholesale price provided prices for 99.9% of physician-dispensed drug claims, while Medi-Cal, the current primary physician-dispensed drug benchmark provided prices for a lower percentage (92.7%) of claims. The CAWCS prices were equivalent to 49% of the average wholesale price, 95.5% of Medi-Cal, 126.7% of the wholesale acquisition cost, 266% of the Federal Upper Limit, 64.4% of direct prices, and 197% of national average drug acquisition cost-estimated prices. The CAWCS current Medi-Cal pricing for physician-dispensed drugs is better than all alternatives in terms of price availability, transparency, and budget neutrality, but pricing availability may decrease over time as Medi-Cal moves to managed care. National average drug acquisition cost is the next best alternative, but it requires combinations of pricing benchmarks to maximize its price availability.

Swing Pricing and Fragility in Open-end Mutual Funds

How to prevent runs on open-end mutual funds? In recent years, markets have observed an innovation that changed the way open-end funds are priced. Alternative pricing rules (known as swing pricing) adjust funds' net asset values to pass on funds' trading costs to transacting shareholders. Using unique data on investor transactions in U.K. corporate bond funds, we show that swing pricing eliminates the first-mover advantage arising from the traditional pricing rule and significantly reduces redemptions during stress periods. The stabilizing effect is internalized particularly by institutional investors and investors with longer investment horizons. The positive impact of alternative pricing rules on fund flows reverses in calm periods when costs associated with higher tracking error dominate the pricing effect.

Development of Demand Response Energy Management Optimization at Building and District Levels Using Genetic Algorithm and Artificial Neural Network Modelling Power Predictions

Demand Response (DR) is a fundamental aspect of the smart grid concept, as it refers to the necessary open and transparent market framework linking energy costs to the actual grid operations. DR allows consumers to directly or indirectly participate in the markets where energy is being exchanged. One of the main challenges for engaging in DR is associated with the initial assessment of the potential rewards and risks under a given pricing scheme. In this paper, a Genetic Algorithm (GA) optimisation model, using Artificial Neural Network (ANN) power predictions for day-ahead energy management at the building and district levels, is proposed. Individual building and building group analysis is conducted to evaluate ANN predictions and GA-generated solutions. ANN-based short term electric power forecasting is exploited in predicting day-ahead demand, and form a baseline scenario. GA optimisation is conducted to provide balanced load shifting and cost-of-energy solutions based on two alternate pricing schemes. Results demonstrate the effectiveness of this approach for assessing DR load shifting options based on a Time of Use pricing scheme. Through the analysis of the results, the practical benefits and limitations of the proposed approach are addressed.

Energy worldviews: Engaging consumers by aligning rate design strategies with personal choice

Rate design serves objectives of cost recovery, market animation, and customer incentives. Yet in the quest to find the ‘perfect equitable rate,’ many rate designers and pilots overlook the diversity of consumer attitudes. AMI enables not only interval monitoring and controls, it allows alternative pricing plans, payment options, device adoption, and generation mixes reflecting individual priorities. Connecting consumer attitudes with a portfolio approach helps regulators and utilities achieve specific goals while improving satisfaction and engagement.

Analyzing Bank Overdraft Fees with Big Data

In 2012, consumers paid $32 billion in overdraft fees, representing the single largest source of revenue for banks from demand deposit accounts during this period. Owing to consumer attrition caused by overdraft fees and potential government regulations to reform these fees, financial institutions have become motivated to investigate their overdraft fee structures. Banks need to balance the revenue generated from overdraft fees with consumer dissatisfaction and potential churn caused by these fees. However, no empirical research has been conducted to explain consumer responses to overdraft fees or to evaluate alternative pricing strategies associated with these fees. In this research, we propose a dynamic structural model with consumer monitoring costs and dissatisfaction associated with overdraft fees. We apply the model to an enterprise-level data set of more than 500,000 accounts with a history of 450 days, providing a total of 200 million transactions. We find that consumers heavily discount the future and potentially overdraw because of impulsive spending. However, we also find that high monitoring costs hinder consumers’ effort to track their balance accurately; consequently, consumers may overdraw because of rational inattention. The large data set is necessary because of the infrequent nature of overdrafts; however, it also engenders computational challenges, which we address by using parallel computing techniques. Our policy simulations show that alternative pricing strategies may increase bank revenue and improve consumer welfare. Fixed bill schedules and overdraft waiver programs may also enhance social welfare. This paper explains consumer responses to overdraft fees and evaluates alternative pricing strategies associated with these fees. The online appendices are available at https://doi.org/10.1287/mksc.2018.1106 .

Why Markdown as a Pricing Modality?

AboutSectionsView PDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked InEmail Go to Section HomeManagement ScienceVol. 65, No. 5 Why Markdown as a Pricing Modality?Elodie Adida , Özalp Özer Elodie Adida , Özalp Özer Published Online:20 Sep 2018https://doi.org/10.1287/mnsc.2018.3046AbstractMarkdown as a pricing modality is ubiquitous in retail whereas everyday low price (EDLP) remains relatively rare (despite its several advantages, such as simplicity). This paper explores whether and why retailers can use either of these pricing modalities as an effective defense against a competitor entering the market with the alternative pricing modality. Various studies have shown that consumers are strategic and heterogeneous in their valuation of a product. Consumers are also shown to be regret-prone, and anticipation of regret affects their purchase decisions. Consumers experience availability regret when they are unable to purchase products due to stockouts and high-price regret when they miss an opportunity to purchase products at low prices. Considering such factors, consumers decide whether, when, and from which retailer to purchase the product. In such a market environment, we find that the possible entry of a competitor should deter retailers from using the EDLP pricing modality but not markdown. We also identify a new reason for the markdown retailer to ration stock (in addition to the reason for discouraging consumers to wait for the markdown). In particular, we show that the markdown retailer can use inventory rationing to preclude a cutthroat competition and bankruptcy after the entry of an EDLP retailer. We also quantify how consumer regret affects both retailers’ decisions and resulting profits. In particular, in a competitive market, the EDLP retailer cannot simply disregard consumers’ availability and high-price regret (even when it stocks ample inventory and does not discount prices). We show that high-price regret and availability regret have complementary effects on the markdown retailer’s rationing strategy and the EDLP retailer’s price decision. Finally, using a proprietary price data set from a large department store, we show that ignoring regret factors causes the markdown retailer to leave up to 20% of its profits on the table. In addition, in a competitive market, the markdown retailer rations too aggressively when regret is ignored and, as a result, leaves some of the forgone profit to its competitor—the EDLP retailer. The retail industry is often characterized by its slim profit margins. In such an environment, the aforementioned results also suggest that retailers should seriously consider investing in developing the capacity to estimate and quantify the role of regret in consumers’ purchase decisions.Data and the online appendix are available at https://doi.org/10.1287/mnsc.2018.3046.This paper was accepted by Serguei Netessine, operations management. Previous Back to Top Next FiguresReferencesRelatedInformationCited byOptimizing mixed bundle pricing strategy: Advance selling and consumer regretOmega, Vol. 115Buy-One-Get-One Promotions in a Two-Echelon Supply ChainYuefeng Li, Moutaz J. Khouja, Jingming Pan, Jing Zhou13 December 2022 | Management Science, Vol. 0, No. 0High-Low Promotion Policies for Peak-End Demand ModelsTamar Cohen-Hillel, Kiran Panchamgam, Georgia Perakis8 August 2022 | Management Science, Vol. 0, No. 0Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing10 December 2019 | Journal of Business Ethics, Vol. 170, No. 4 Volume 65, Issue 5May 2019Pages 1949-2443 Article Information Supplemental Materials Metrics Information Received:September 15, 2016Accepted:December 12, 2017Published Online:September 20, 2018 Copyright © 2018, INFORMSCite asElodie Adida, Özalp Özer (2018) Why Markdown as a Pricing Modality?. Management Science 65(5):2161-2178. https://doi.org/10.1287/mnsc.2018.3046 Keywordspricingmarkdowneveryday low pricecompetitionregretPDF download

Using food prices and consumption to examine Chinese cost of living

AbstractThis paper considers two approaches to examining potential bias in China's consumer price index: (i) inferring true changes in cost of living from consumer behaviour; and (ii) creating alternative price indices to compare with official indices. For (i), our semi‐parametric estimates agree with the recent finding of a large understatement in increases to the true cost of living. For (ii), we focus on food prices and explore potential causes of bias. We find some evidence of a new‐good bias. China's large‐scale migration also causes changes in the cost of living that are not reflected in the consumer price index.

Improving Usage Metrics for Pay-per-Use Pricing with IoT Technology and Machine Learning

Overview: Servitization has attracted significant attention from the manufacturing industry for its potential to provide competitive advantage. Advanced services require alternative pricing models, such as pay-per-usage (PPU), but many support goods fail to produce countable output units, leaving few choices for billing metrics. However, this article proposes an improved set of usage metrics based on Internet of Things (IoT) technology and machine learning. These metrics capture value-in-use and allow for more accurate assessment of the depreciation, providing benefits to both the manufacturer and the customer and supporting the extension of PPU models to a wider range of industrial support goods and product-service systems.

Choice of High Occupancy/Toll Lanes under Alternative Pricing Strategies

High occupancy/toll (HOT) lanes typically vary tolls charged to single occupant vehicles, with the toll increasing during congested periods. The toll is usually tied to time of day or to the density of vehicles in the HOT lane. The purpose of raising the toll with congestion is to discourage demand sufficiently to maintain travel speeds in the HOT lane. However, it has been demonstrated that the HOT toll may act as a signal of downstream congestion (in both general purpose (GP) and HOT lanes), causing an increase in demand for the HOT lane, at least at lower prices. This paper develops a model of lane choice to evaluate alternative HOT lane pricing strategies, including the use of GP density, to more accurately reflect the value of the HOT lane. In addition, the paper explores the potential effect these strategies would have on the HOT lane vehicle share through a partial equilibrium analysis. This analysis demonstrates the change in demand elasticity with price, showing the point at which drivers switch from a positive to negative elasticity.

Matchmaker Competition and Technology Provision

Matchmaking is a complex process that requires considerable expertise. Matchmakers in various industries often advertise proprietary technologies that presumably help users find an ideal match in a short time. However, matchmakers may have incentives to provide suboptimal matchmaking services so that users remain clients longer and pay more fees. This article considers a matchmaking market with network effects and strategic consumers and analyzes under what conditions matchmakers would offer more effective versus less effective matchmaking services. The authors find that stronger pricing power paradoxically leads to lower technology provision when consumers have high valuation for the matchmaking service. Moreover, network effects typically encourage matchmakers to retain the users in the market to create positive externalities, which can result in less precise matchmaking. In addition, consumer patience prompts competing matchmakers to implement ineffective technology. In two extensions, the authors explore asymmetric two-sided markets and discuss the impacts of alternative pricing schemes on technology provision.

The impact of alternative pricing methods for drugs in California Workers' Compensation System: Fee-schedule pricing.

IntroductionCalifornia’s Workers’ Compensation System (CAWCS) Department of Industrial Relations questioned the adequacy of the current Medi-Cal fee-schedule pricing and requested analysis of alternatives that maximize price availability and maintain budget neutrality.ObjectivesTo compare CAWCS pharmacy-dispensed (PD) drug prices under alternative fee schedules, and identify combinations of alternative benchmarks that have prices available for the largest percentage of PD drugs and that best reach budget neutrality.MethodsClaims transaction-level data (2011–2013) from CAWCS were used to estimate total annual PD pharmaceutical payments. Medi-Cal pricing data was from the Workman’s Compensation Insurance System (WCIS). Average Wholesale Prices (AWP), Wholesale Acquisition Costs (WAC), Direct Prices (DP), Federal Upper Limit (FUL) prices, and National Average Drug Acquisition Costs (NADAC) were from Medi-Span. We matched National Drug Codes (NDCs), pricing dates, and drug quantity for comparisons. We report pharmacy-dispensed (PD) claims frequency, reimbursement matching rate, and paid costs by CAWCS as the reference price against all alternative price benchmarks.ResultsOf 12,529,977 CAWCS claims for pharmaceutical products 11.6% (1,462,814) were for PD drugs. Prescription drug cost for CAWCS was over $152M; $63.9M, $47.9M, and $40.6M in 2011–2013. Ninety seven percent of these CAWCS PD claims had a Medi-Cal price. Alternative mechanisms provided a price for fewer claims; NADAC 94.23%, AWP 90.94%, FUL 73.11%, WAC 66.98%, and DP 14.33%. Among CAWCS drugs with no Medi-Cal price in PD claims, AWP, WAC, NADAC, DP, and FUL provided prices for 96.7%, 63.14%, 24.82%, 20.83%, and 15.08% of claims. Overall CAWCS paid 100.52% of Medi-Cal, 60% of AWP, 97% of WAC, 309.53% of FUL, 103.83% of DP, and 136.27% of NADAC.ConclusionsCAWCS current Medi-Cal fee-schedule price list for PD drugs is more complete than all alternative fee-schedules. However, all reimbursement approaches would require combinations of pricing benchmarks. We suggest keeping primary reimbursement at 100% of Medi-Cal and for drugs without a primary Medi-Cal price calculating the maximum fee as 60% of AWP and then 97% of WAC. Alternatively, we suggest using NADAC as a primary fee-schedule followed by either 60% AWP and 97% WAC or AWP-40% for drugs with no NADAC price. Fee-schedules may not offer the best price and a formulary approach may provide more flexibility.

Sectoral Heterogeneity in Nominal Rigidities in Korea: Implications for Monetary Policy

This paper documents how the frequency of price changes differs across sectors in Korea and what implications such heterogeneity may have for monetary policy. We find that under heterogeneity: i) monetary policy has larger and more persistent real effects; ii) it is welfare improving to stabilize an alternative (optimal) price index that places disproportionately larger weights on stickier sectors, rather than the Consumer Price Index; iii) the central bank, targeting such an alternative index, should move nominal interest rates more slowly, which may provide a justification for the gradualism in monetary policy; and iv) the condition for equilibrium determinacy is different. Overall, our results suggest that it is potentially important for the monetary authority to take into account how firms' pricing behaviors differ across sectors in the design of monetary policy.

Economic feasibility of an augmentative biological control industry in Niger

Farmers in Niger are vulnerable to high millet yield losses due to the millet head miner, Heliocheilus albipunctella De Joannis (Lepidoptera: Noctuidae), for which pest control options are limited. Researchers have developed a procedure to multiply and spread an augmentative biological control agent Habrobracon hebetor Say (Hymenoptera: Braconidae) which is effective in limiting millet yield losses due to the pest. This study assesses the economic viability of small businesses to produce and sell biological control agents. It analyzes the profitability of the businesses under alternative pricing regimes given estimated costs to produce and distribute biological control agents. The economic assessment provides budget analysis for potential businesses and discusses options for scaling, price setting, and organizing. Our study suggests that the small H. hebetor industry should turn a profit in Niger at relatively low prices for the biological control agents of $3.00-$4.00 per bag with 15 bags needed per village. Competitive wages are achievable for the businesses that sell to at least 13 villages. Each business would hire three workers from late May to late August. Commercialization of H. hebetor would generate opportunities for wide geographic distribution of the technology on a sustainable basis in Niger.