Emerging Retailer Pricing Trends and Practices Ruth Bolton and Venkatesh Shankar
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Pricing of Digital Products and Services in the Manufacturing Ecosystem
Pricing of digital products and services in the manufacturing ecosystem From cost-based to value-based pricing 02 Pricing of digital products and services in the manufacturing ecosystem | From cost-based to value-based pricing Executive summary 04 The traditional vs. digital approach to pricing 06 Pricing strategies in a digital ecosystem 12 Key considerations for strategic pricing decisions 18 Next step: How to get the pricing right? 20 Legal considerations 22 Conclusion 24 Endnotes 26 Contacts 28 03 Executive summary Digital products and services are becoming their specific role within the network in a increasingly important for discrete broader sense rather than relying solely manufacturers looking to complement on internal supply chains when it comes to their core business, stabilize profits and pricing and positioning their digital prod- generate new revenue streams. Today’s ucts and services in the market. industrial companies already generate 20–30 percent of their profits in the after This white paper addresses these chal- sales and service business, and the trend lenges, focusing on the pricing of is toward more digital solutions. To exploit digital goods and services in discrete the value derived from digitalized products manufacturing. The objective is to help and services, manufacturing companies manufacturing companies better under- need to understand what makes digital stand the pricing mechanisms in a digital products and services unique and how the ecosystem and to identify potential pricing market dynamics are changing in the new, scenarios for their digital business: platform-driven manufacturing ecosystem. 1. How do pricing mechanisms work in a Digital products and services differ digital ecosystem and why are traditional fundamentally from traditional industrial pricing approaches no longer feasible? products, mainly in terms of their cost structures and the customer's willingness 2. -
Dynamic Pricing When Consumers Are Strategic: Analysis of a Posted Pricing Scheme
OPERATIONS RESEARCH INFORMS Vol. 00, No. 0, Xxxxx 0000, pp. 000{000 doi 10.1287/xxxx.0000.0000 issn 0030-364X j eissn 1526-5463 j 00 j 0000 j 0001 °c 0000 INFORMS Dynamic pricing when consumers are strategic: Analysis of a posted pricing scheme Sriram Dasu Marshall School of Business, University of Southern California, [email protected], Chunyang Tong Marshall School of Business, University of Southern California, [email protected], We study dynamic pricing policies for a monopolist selling perishable products over a ¯nite time horizon to buyers who are strategic. Buyers are strategic in the sense that they anticipate the ¯rm's pricing policies. We are interested in situations in which auctions are not feasible and in which it is costly to change prices. We begin by showing that unless strategic buyers expect shortages dynamic pricing will not increase revenues. We investigate two pricing schemes that we call posted and contingent pricing. In the posted pricing scheme at the beginning of the horizon the ¯rm announces a set of prices. In the contingent pricing scheme price evolution depends upon demand realization. Our focus is on the posted pricing scheme because of its ease of implementation. In equilibrium, buyers will employ a threshold policy in both pricing regimes i.e., they will buy only if their private valuations are above a particular threshold. We show that a multi-unit auction with a reservation price provides an upper bound for the expected revenues for both pricing schemes. Numerical examples suggest that a posted pricing scheme with two or three price changes is enough to achieve revenues that are close to the upper bound. -
Smart Pricing
01_013149418X_intro.qxp 2/11/10 8:37 AM Page 1 Introduction: Fingerprints of the Invisible Hand After a long season of back-breaking labor seeding, feeding, and growing a crop, a farmer would never say, “Time to harvest—let’s take it easy.” If anything, the farmer would get up even earlier and go to bed even later to make sure that every last grain was harvested. Yet supposedly sophisticated companies, run by some of the best-edu- cated people in the world, neglect what peasants have known by instinct for thousands of years. They work hard thinking about, grow- ing, and finding markets for their product but then pay scant atten- tion to the decision that determines what all that hard work yields the company: setting the price. Despite the critical function prices play in corporate profitability, we find that managers with pricing responsibilities do not usually think systematically about their pricing strategies. Most pricing deci- sion makers never look for a strategy that could yield their product’s maximum value. According to one study, only a tiny number of firms have “both a pricing strategy and research to support it.” When it comes to pricing, some estimated that only about 8% of American businesses can be considered “sophisticated players.”1 Oddly, nobody seems bothered by this state of affairs. Many exec- utives we talk to about prices say, “We don’t set prices. The market does!” As economists, we are not sure what this statement means. “Who is the market, then?” we press them. 1 01_013149418X_intro.qxp 2/11/10 8:37 AM Page 2 2 SMART PRICING To our mind, this is a reasonable question. -
Dynamic Pricing Strategies for Multi-Product Revenue Management
MANUFACTURING & SERVICE OPERATIONS MANAGEMENT informs ® Vol. 8, No. 2, Spring 2006, pp. 136–148 doi 10.1287/msom.1060.0105 issn 1523-4614 eissn 1526-5498 06 0802 0136 © 2006 INFORMS Dynamic Pricing Strategies for Multiproduct Revenue Management Problems Constantinos Maglaras Columbia Business School, Columbia University, 409 Uris Hall, 3022 Broadway, New York, New York 10027, [email protected] Joern Meissner Lancaster University Management School, Lancaster University, Room A48, Lancaster LA1 4XY, United Kingdom, [email protected] onsider a firm that owns a fixed capacity of a resource that is consumed in the production or delivery of Cmultiple products. The firm strives to maximize its total expected revenues over a finite horizon, either by choosing a dynamic pricing strategy for each product or, if prices are fixed, by selecting a dynamic rule that controls the allocation of capacity to requests for the different products. This paper shows how these well- studied revenue management problems can be reduced to a common formulation in which the firm controls the aggregate rate at which all products jointly consume resource capacity, highlighting their common structure, and in some cases leading to algorithmic simplifications through the reduction in the control dimension of the associated optimization problems. In the context of their associated deterministic (fluid) formulations, this reduction leads to a closed-form characterization of the optimal controls, and suggests several natural static and dynamic pricing heuristics. These are analyzed asymptotically and through an extensive numerical study. In the context of the former, we show that “resolving” the fluid heuristic achieves asymptotically optimal performance under fluid scaling. -
Pricing Strategies in Online & Offline Retailing
Pricing Strategies in Online & Offline Retailing Gottfried Gruber Institute for Management Information Systems Vienna University of Economics and Business Administration Augasse 2–6, 1090 Wien [email protected] Supervisor Hans Robert Hansen Institute for Management Information Systems Vienna University of Economics and Business Administration Augasse 2–6, 1090 Wien [email protected] Fall 2008 Abstract The thesis deals with pricing strategies for multichannel retailers, espe- cially traditional stores which additionally manage an online shop. The problem of integrating two sales channels and applying a well-suited pricing strategy is still an emergent question. This work develops a stochastic model to represent consumer behavior on pricing. On the one hand the model contains two probability functions which render consumers’ reservation prices for each individual channel. On the other hand the stochastic model is based on numerous distributions which rep- resent switching probabilities from and to each separate channel. The various distribution functions will be estimated from the results of a sur- vey. To highlight differences of pricing strategies due to several product categories a cross comparisons of books, clothes and digital cameras will be presented. The results show that there are differences in multichannel pricing of the various products. These inequalities stem from consumers’ perceptions of the sales channels. For each product a separate sales channel is pre- ferred by consumers. Therefore, one channel exhibits some advantage versus the alternative channels. This advantage is reflected in different pricing strategies. Further appropriate marketing strategies could help a firm to counter discounting by its competitors. So firms should keep an eye on the reservation price structure of its consumers as well as their demanded marketing activities. -
Zone Pricing in Retail Oligopoly
ZONE PRICING IN RETAIL OLIGOPOLY By Brian Adams and Kevin R. Williams February 2017 COWLES FOUNDATION DISCUSSION PAPER NO. 2079 COWLES FOUNDATION FOR RESEARCH IN ECONOMICS YALE UNIVERSITY Box 208281 New Haven, Connecticut 06520-8281 http://cowles.yale.edu/ ZONE PRICING IN RETAIL OLIGOPOLY Brian Adams Kevin R. Williams Bureau of Labor Statistics∗ Yale Universityy February 2017z Abstract We quantify the welfare effects of zone pricing, or setting common prices across distinct markets, in retail oligopoly. Although monopolists can only increase profits by price discriminating, this need not be true when firms face competition. With novel data covering the retail home improvement industry, we find that Home Depot would benefit from finer pricing but that Lowe’s would prefer coarser pricing. The use of zone pricing softens competition in markets where firms compete, but it shields con- sumers from higher prices in markets where firms might otherwise exercise market power. Overall, zone pricing produces higher consumer surplus than finer pricing discrimination does. JEL Classification: C13, L67, L81 ∗[email protected] [email protected] zA previous version of this paper circulated under the title, "Zone Pricing and Strategic Interaction: Evidence from Drywall." We thank the seminar participants at the University of Minnesota, California State University-East Bay, Marketing Science, University of Wisconsin-Madison, Yale University, Econometric Society Summer Meetings, University of Massachusetts-Amherst, Bureau of Labor Statistics, Department of Justice, Federal Trade Commission, University of Pennsylvania, and the AEA Winter Meetings for useful comments. We thank Bonnie Murphie and Ryan Ogden for their assistance with Bureau of Labor Statistics data. -
Strategy-Price Discrimination
LECTURE 7- STRATEGY-PRICE DISCRIMINATION Konstantinos Kounetas School of Business Administration Department of Economics Master of Science in Applied Economic Analysis Introduction • What is actually a strategy? Which factors affect firm’s strategies? • Price discrimination is present whenever two or more similar goods are sold at prices that are in different ratios to marginal costs.” Stigler (1987) • Necessary conditions for PD: • Firm must have some market power • Must have ability to sort consumers (consumers with varying elasticities of demand) • Must be able to prevent resale, prevent or limit arbitrage. • The basic theory of price discrimination is the theory of monopoly, applied to more than one market or group (McAfee, 2008) Defining Strategy • Business strategy describes the way in which a firm addresses its fundamental challenges over the medium and long tern. Usually, is applied to the decision making processes of the senior management team but it can be also applied at all levels. • Series of actions, decisions and obligations which lead to the firm gaining a competitive advantage and exploit its core competencies. • Five P’s of business strategy (Mintzber, 1987) 1. A plan 2. A ploy 3. A pattern of behavior 4. A position with respect to others 5. A perspective Strategic Management-Analysis 1.Strategic analysis 2.Strategic choice 3. Strategic implementation Stakeholders views Corporate Big vs Small business governance Manufacturing vs Service Domestic vs Multinational Organizational Private vs public purpose Business Ethics Cultural context Strategic Analysis-5P’s (Porter) • The bargaining power of suppliers • The bargaining power of buyers • The threat of potential new entrants • The threat of substitutes Potential Entrants • The extent of competitive rivalry Industry Competitors Buyers Rivalry among existing Suppliers firms Substitute Products Strategic Choice • Theories of strategic choice falls in two main categories: market based and resource based. -
Dynamic Pricing Recognition on E-Commerce Platforms with VAR Processes
forecasting Article Dynamic Pricing Recognition on E-Commerce Platforms with VAR Processes Alexander Faehnle 1,* and Mariangela Guidolin 2 1 Alten Italia, 35131 Padua, Italy 2 Department of Statistical Sciences, University of Padua, 35121 Padua, Italy; [email protected] * Correspondence: [email protected] Abstract: In an environment such as e-commerce, characterized by the presence of numerous agents, competition based on product characteristics is a very important aspect. This paper proposes a model based on vector autoregressive processes (VAR) and Lasso penalization to detect and examine the dynamics that govern real-time price competition in electronic marketplaces. Employing this model, an empirical study was performed on the price trends of smartphone models on the major electronic sales platforms of the Italian market. The proposed model detects real-time price variations in single vendors, based on the variations of their direct competitors. The statistical method adopted in this analysis may be useful for e-commerce companies that conduct market analyses of competitors’ pricing strategies. Keywords: dynamic pricing; e-commerce; VAR process; price competition; lasso penalization JEL Classification: C01; C5; C32 Citation: Faehnle, A.; Guidolin, M. Dynamic Pricing Recognition on 1. Introduction E-Commerce Platforms with VAR In recent years, the volume of sales on e-commerce platforms has grown considerably. Processes. Forecasting 2021, 3, Today, it is not uncommon to find many offers with different prices for the same product at 166–180. https://doi.org/10.3390/ the same time. Thus, online real-time pricing has assumed a role of fundamental strategic forecast3010011 importance. On one hand, companies have to constantly adjust their price levels based on competitors’ prices for the same products to appeal to customers, without losing revenue Academic Editor: Alessia Paccagnini margins. -
(Mixed) Strategy in Oligopoly Pricing: Evidence from Gasoline Price Cycles Before and Under a Timing Regulation
Wednesday Nov 18 2009 02:17 PM JPE v117n6 2008149 VLONGAWA (Mixed) Strategy in Oligopoly Pricing: Evidence from Gasoline Price Cycles Before and Under a Timing Regulation Zhongmin Wang Northeastern University This paper studies oligopoly firms’ dynamic pricing strategies in a gasoline market before and after the introduction of a unique law that constrains firms to set price simultaneously and only once per day. The observed gasoline pricing behavior, both before and under the law, is well captured by the Edgeworth price cycle equilibrium in the Maskin and Tirole dynamic oligopoly model. My results highlight the importance of price commitment in tacit collusion. I also find evidence that the price leadership outcome under the law is better predicted by mixed strategies play than by alternative hypotheses. I. Introduction This paper examines the oligopoly problem by studying firms’ dynamic pricing strategies in a retail gasoline market before and after the intro- duction of a unique law that constrains firms to set price simultaneously and only once per day. The observed gasoline pricing behavior, both before I thank the editor and two anonymous referees for their comments, which significantly improved this paper. I am especially grateful to Jim Dana for many helpful and stimulating discussions. I thank Kamran Dadkhah, Juan Dubra, John Kwoka, Christian Rojas, and seminar participants at Clark University for their comments on an earlier version of this paper. I also thank Simon Goss, Sean Isakower, Shu Li, and Jingjing Yang for their assistance with collecting data; Allan Price at Informed Sources; staff members at the Western Aus- tralia Department of Consumer and Employment Protection; the owners of three gasoline retailers for providing data; several industry participants for explaining the Perth gasoline market and providing evidence on the special forms of vertical restraints documented in this paper; and the Faculty of Business and Economics at Monash University for providing financial support. -
Supermarket Pricing Strategies
informs Vol. 27, No. 5, September–October 2008, pp. 811–828 ® issn 0732-2399 eissn 1526-548X 08 2705 0811 doi 10.1287/mksc.1080.0398 ©2008 INFORMS Supermarket Pricing Strategies Paul B. Ellickson Department of Economics, Duke University, Durham, North Carolina 27708, [email protected] Sanjog Misra William E. Simon School of Business Administration, University of Rochester, Rochester, New York 14627, [email protected] ost supermarket firms choose to position themselves by offering either everyday low prices (EDLP) across Mseveral items or offering temporary price reductions (promotions) on a limited range of items. While this choice has been addressed from a theoretical perspective in both the marketing and economic literature, relatively little is known about how these decisions are made in practice, especially within a competitive envi- ronment. This paper exploits a unique store level data set consisting of every supermarket operating in the United States in 1998. For each of these stores, we observe the pricing strategy the firm has chosen to follow, as reported by the firm itself. Using a system of simultaneous discrete choice models, we estimate each store’s choice of pricing strategy as a static discrete game of incomplete information. In contrast to the predictions of the theoretical literature, we find strong evidence that firms cluster by strategy by choosing actions that agree with those of its rivals. We also find a significant impact of various demographic and store/chain characteristics, providing some qualified support for several specific predictions from marketing theory. Key words: EDLP; promotional pricing; positioning strategies; supermarkets; discrete games History: Received: March 22, 2006; accepted: February 27, 2008; processed by David Bell. -
Dynamic Pricing Strategies and Customer Heterogeneity
The more the merrier? Understanding how travel frequency shapes willingness to pay Marta Nieto Garcíaa, Pablo A. Muñoz Gallegob, Óscar Gonzalez Benitoc Keywords: willingness to pay, travel frequency, reference price, dynamic pricing, room rates a University of Portsmouth, Faculty of Business and Law, Richmond Building, Portland Street, Portsmouth PO1 3DE. Telf. +44 02392 844028 Corresponding author: [email protected] b Universidad de Salamanca, Instituto Multidisciplinar de Empresa, Edificio FES Campus Unamuno, 37007 Salamanca, Spain. Telf. +34 923294500 (3127) [email protected] c Universidad de Salamanca, Instituto Multidisciplinar de Empresa, Edificio FES Campus Unamuno, 37007 Salamanca, Spain. Telf. +34 923294500 (3008) [email protected] The more the merrier? Understanding how travel frequency shapes willingness to pay Abstract Customers’ evaluation of hotel prices has received increasing attention in hospitality research. Beyond the specific attributes of the offer, internal norms related to prior experiences affect customers’ response to price. Drawing on the behavioral price literature, this study investigates the effect of travel frequency and reference price on the formation of travelers’ willingness to pay (WTP) for accommodation. The study presents a novel methodological approach introducing the concept of instantaneous indirect effect. Results offer support for an inverted U-shaped relationship between travel frequency and WTP, mediated by the internal reference price. WTP reaches its peak when the customer has booked an accommodation six times in the past two-year period. The findings provide clear implications for practitioners. Monitoring customers’ travel frequency and integrating it into dynamic pricing models will create a better alignment of room rates with travelers’ WTP, which will make revenue management techniques more customer-centric and, ultimately, enhance profitability. -
Pricing of Interrelated Goods in Oligopoly
IISSEETT WORKING PAPER SERIES WP 014‐08 OCTOBER 2008 Pricing Interrelated Goods in Oligopoly Sandro Shelegia The International School of Economics at Tbilisi State University (ISET) is supported by BP, the Government of Georgia, the Norwegian Ministry of Foreign Affairs, Higher Education Support Program of the Open Society Institute, the Swedish International Development Agency and the World Bank. International School of Economics at Tbilisi State University 16 Zandukeli Street, Tbilisi 0108, Georgia www.iset.ge e‐mail: [email protected] Pricing Interrelated Goods In Oligopoly Sandro Shelegia∗ Department of Economics and Business Universitat Pompeu Fabra This Draft: July 31, 2008 Abstract In this paper we propose a two-good model of price competition in an oligopoly where the two goods can be complements or substitutes and each retailer has a captive consumer base `ala Burdett and Judd(1983). We find that the symmetric Nash Equilibrium of this model features atomless pricing strategies for both goods. When the two goods are complements the prices charged by any retailer are, at least locally, negatively correlated so if one of the goods is priced high the other one is on a discount. This finding is supported by an empirical observation that simultaneous discounts of complements are infrequent. In contrast, if the goods are substitutes or independently valued the prices will be randomized independently unless the less valuable substitute is not sold at all. In the case of complements the retailers earn higher profit relative to the case of selling both goods only as a bundle. The ability to \discriminate" between the captives and the shoppers through keeping the sum of the two prices high while setting one of the prices low drives the result.