Revenue management for make-to-order manufacturing systems with a real-life application

Abstract

Due to successful applications of revenue management in the airline industry, in recent years, there has been a growing interest to adopt revenue management in make-to-order (MTO) manufacturing systems. Several interrelated decision problems such as order acceptance/rejection, short-term capacity planning, due date assignment, and order scheduling need to be studied simultaneously in order to manage revenues effectively in MTO manufacturing systems. Both the producer’s and customer’s requirements need to be taken into account through some negotiation mechanisms that are sensitive to the service-level reputation of the manufacturing companies. In this article, we propose a new dynamic bid price–based revenue management model that considers all of the aforementioned decision problems simultaneously. A simulation optimization approach is utilized in order to determine the best possible values of control parameters for bid price, due date assignment, and price increment/reduction mechanisms. The performance of the proposed integrated revenue management model is tested on both a hypothetical example and a real problem of a bridal gown company. The computational results show that the proposed model provides significant improvements in total revenue compared to other static and dynamic bid price policies.     

Risk averse retail pricing with robust demand forecasting

Good demand estimates are the key to effective pricing decision-making. However, they are subject to a high degree of uncertainty due to various factors that are unpredictable or difficult to model, thus making pricing decisions risky. This research provides a simple proposal for a robust optimization methodology that incorporates both demand uncertainty and the decision maker's degree of risk aversion. Uncertainty is explicitly considered for two coefficients of a linear demand function, price expressions are derived, and a criterion is proposed for defining the degree of risk aversion. The resulting model is also applied to an exponential demand case to better reflect a more realistic retail setting.     

Concurrent pricing and lot sizing for make-to-order contract production

This paper develops a model for the simultaneous (i.e. concurrent) determination of the inventory and pricing policies of a supplier, which produces and supplies a product to a buyer, on the basis of a contractual agreement, calling for the delivery of a specific quantity periodically. Assuming that the customer is rational, i.e. it follows its own optimal purchasing policy, the objective of the supplier is to determine the product's selling price, in conjunction with an appropriate production/inventory policy, so that a predetermined gross profit level is achieved. It is further assumed that the supplier's production batch size is an integer multiple of the buyer's order quantity. In formulating a mathematical model of this situation, the interactions between the product's price, the buyer's economic order quantity and the supplier's selling price, costs and profit are taken into account. For solving this model, a simple iterative algorithm is proposed, which is illustrated through a numerical example. Sensitivity analysis performed on the model demonstrates that it is relatively robust and quite insensitive to errors in estimating the buyer's ordering to carrying cost ratio on the part of the producer.     

Violations of rational choice principles in pricing decisions

Research on behavioral and psychological aspects of pricing is concerned with violations of rationality. This paper presents a comprehensive overview of the current literature by highlighting those studies that have specific relevance for industrial pricing. I hereby examine two different perspectives. First, by taking the customer perspective, I analyze under which circumstances customer purchase decisions violate basic principles of rational choice. Second, by taking the perspective of managers, I examine which biases affect the process of price setting within firms. This overview meaningfully advances industrial pricing theory and practice: It allows both customers and managers to guard themselves against widely diffused traps in decision making. It also enables managers to favorably influence customer perceptions of value and price without actually changing the price. Finally, by pulling together a number of different research areas into a more parsimonious framework and a tighter narrative, this framework offers systematic directions for future research.     

The Urban Homeowner's Residential Location Decision in an Asset-Pricing Context

Homeowners determine the maximum site bid price for homeowner housing within a two-period expected-utility model. The bid price is a function of the expected cash flows to sites, the quantity of housing consumed and a relocation option. The bid price is derived in the general case as a function of the homeowner's portfolio risk, including the total risk to the site, and the market price of risk. The bid price is derived under a spatial measure as a function of distance from an arbitrary location. Specific results are obtained when the household experiences log-linear utility for housing and other goods. Use of the market price of risk simplifies analytical solutions to the bid price equation.     

Best Practices for New Product Pricing: Impact on Market Performance and Price Level under Different Conditions

To date, research on new product pricing has predominantly been approached as a choice between market skimming and penetration pricing. Despite calls for research that addresses other complexities in new product pricing, empirical research responding to these calls remains scarce. This paper examines three managerial price‐setting practices for new products, i.e., value‐informed, competition‐informed, and cost‐informed pricing. By engaging in these practices, managers can develop and compare quantifications in order to attain an introduction price for the product. The authors draw on consumer price perception literature, Monroe's pricing discretion model, and numerical cognition literature to develop hypotheses about the impact of price‐setting practices on new product market performance and price level. By studying the effects on market performance and price level, the paper provides insights that may help explain the growth of new products and address the problems of underpricing. The hypotheses are tested in a management survey of 144 production and service companies. The results indicate which pricing practices are superior for the achievement of either higher market performance or higher prices in specific product and market conditions. Whereas value‐informed pricing has an unambiguous positive impact on relative price level and market performance, the results also suggest that in many cases engaging in value‐informed pricing is not enough. The effects of cost‐informed and competition‐informed pricing may differ depending upon the objective (market performance or higher prices), product conditions (product advantage and relative product costs), and market condition (competitive intensity). Engaging in inappropriate pricing practices leads to a decline in new product performance. Moreover, bad pricing practices make the positive effect of product advantage on the outcome variables disappear. The latter finding suggests that companies can jeopardize their efforts and investments in the new product development process if they engage in the wrong price‐setting practices. The findings imply that managers should consider different factors in new product pricing. First, when launching a new product, they should determine their explicit pricing objective, either stressing market performance or a higher price level. To determine the most appropriate pricing practices, however, they should next assess their situation in terms of product advantage, relative product costs, and competitive intensity. Together with the pricing objective, these conditions determine the best pricing practice. On a higher level, the findings imply that companies should invest in knowledge development in order to engage in the appropriate pricing practices for each product launch.     

The Role of Value‐Informed Pricing in Market‐Oriented Product Innovation Management*

Although the positive effect of a market orientation on new product success is widely accepted and the market orientation literature has increased its understanding of how a market orientation leads to performance, the extant literature has overlooked the role of value‐informed pricing in the relationship. Value‐informed pricing is a pricing practice in which the decision makers base the price of the new product on the customers' perceptions of the benefits that the product offers and how these benefits are traded by customers against the price (that has yet to be determined). Considering that pricing mistakes may hit hard on the profitability of product innovations, it is important to firms to have a good understanding of its role. This study develops a framework in which value‐informed pricing is integrated in the relationship between market orientation and new product performance. A distinction is made between customer and competitor orientations, and relative product advantage is also included in the conceptual model. The model is tested on data obtained from managers based on a cross sectional sample of 144 firms. The respondents were involved in a decision‐making process of the pricing of a new product. The model is tested using structural equations modeling. The results show that value‐informed pricing has a strong effect on new product performance. It also reveals that each component of a market orientation fulfills a specific role in a market‐oriented organization. Value‐informed pricing is found to have important mediating effects in the market orientation–new product performance relationship. Results show that firms with a strong customer orientation engage in value‐informed pricing and develop superior benefits to customers in an advantageous product. In turn, both value‐informed pricing and relative product advantage positively affect new product market performance. However, no significant effect of competitor orientation on value‐informed pricing is found. Combined with the finding that competitor orientation negatively affects relative product advantage, this suggests that competitor orientation may hurt new product performance when this orientation is not balanced with a strong customer orientation. The results also portray that value‐informed pricing leads to higher product advantage. Interestingly, this relation is contingent on the degree of interfunctional coordination within the firm. This suggests that the relationship between market orientation and new product performance is strongest if firms integrate value‐informed pricing in the new product development process. In this sense, a market‐oriented firm mirrors the customer value perception that makes a trade‐off between benefits and price.     

Customer and retailer rebates under risk aversion

In a supply chain setting, we analyze a manufacturer's customer and retailer rebates, which are sales incentives offered to the end buyers and retailers, respectively. The performance of both rebates is influenced by the retailer's objective and response to the promotion due to his intermediary position in the channel. Earlier studies investigating rebates in distribution channels have traditionally assumed that the retailer is risk neutral with the objective of maximizing expected profits. In our paper, we consider a risk-averse retailer. We formally model risk aversion by adopting the Conditional-Value-at-Risk (CVaR) decision criterion. Using a stochastic and (effective) price dependent demand, we analyze the manufacturer's rebate amount decisions and the retailer's joint inventory and pricing decisions in a game theoretical framework. We provide several structural properties of the objective functions and show monotonicity of the retailer's decisions in the degree of risk aversion. For the case of retailer rebates, we characterize the unique equilibrium, and for the case of customer rebates, we prove the existence of an equilibrium. Using numerical examples, we provide further insights on the impact of risk aversion. For example, given an exogenous wholesale price, we observe a threshold value on the retailer's risk-aversion parameter below (above) which the manufacturer is better off with retailer rebates (customer rebates); implying that the manufacturer's preferred rebate type can be different depending on whether the retailer is risk neutral or sufficiently risk averse.     

Multiproduct Firms' Pricing Behaviour in the Italian Grocery Trade

This paper investigates the determinants of price dispersion between different goods in grocery retailing, as the result of pricing decisions of multiproduct retailers. Demand parameters are generated using the LES system. These are then used to test theoretical predictions about the nature of supermarkets' pricing and consumers' shopping behaviour using disaggregated data from the Italian grocery trade. The empirical results concerning the supply function provide evidence for the existence, in all types of retail organisation, of a monopolistic form of price discrimination. The results are consistent with discrimination due to the exploitation of customers' switching costs.     

Experimenting with purchase history based price discrimination

Many purchases of differentiated goods are repeated, giving sellers the opportunity to engage in price discrimination based upon the shopper's previous behavior by either offering loyalty discounts to repeat buyers or introductory rates to new customers. Recent theoretical work suggests that loyalty discounts can be profitable to sellers when customer preferences are not stationary and sellers can pre-commit to prices for repeat buyers, but otherwise returning customers can be expected to pay the same or more than new buyers. This paper reports behavior in controlled laboratory experiments designed to empirically test the impact of these factors on pricing strategies. The results generally support the comparative static predictions of the theoretical model. When customer preferences are fixed over time, sellers attempt to lure customers from their rival. Price pre-commitment for repeat shoppers when buyer preferences vary over time resulted in modest loyalty pricing, but the discounts are not as prevalent as predicted as sellers rarely price below cost. Behaviorally, price pre-commitment to loyal customers is found to reduce prices overall.     

Engineering New-Product Success: The New-Product Pricing Process at Emerson

Emerson Electric Co. is a diversified manufacturer with $14 billion in sales. The Emerson Price Improvement Team is an internal consulting group that serves the 60+ Emerson divisions. The team's mission is to help divisions achieve their financial and market objectives by providing pricing skills, tools, and project assistance that improve a division's pricing practices. This paper discusses an implementation of the Price Improvement Team's New Product Pricing Process at Fisher-Rosemount, a business unit of Emerson. Fisher-Rosemount is the world's leading supplier of process control systems, and measurement instrumentation. One of the eight Fisher-Rosemount divisions planned to introduce a new process sensor at a price of $2,650. After completing the New Product Pricing Process, Fisher-Rosemount increased the planned sensor price 19%, introducing it at a price of $3,150, resulting in a fifth-year operating profit improvement of $11 million. The New Product Pricing Process enabled the division to gain a detailed understanding of customer perceptions of product value; determine a key design specification for the new product; reduce cannibalization of its existing and highly profitable sensor by positioning the new product to optimize the total product portfolio; predict unit sales, revenue, and profitability for a range of market scenarios; and confidently set the right product price. Achieving optimal revenue and profitability, in a manner consistent with the company's business strategy, is a goal of the process. Equally important, the process ensures that customers receive fair value-based pricing while enabling the supplying company to maintain overall industry price equilibrium.     

Responsive and Proactive Market Orientation and New‐Product Success*

What is the relationship between market orientation and new‐product success? This important question has not been examined adequately to date because the concept of market orientation has been measured too narrowly. The concept of market orientation implies both responsive market orientation, which addresses the expressed needs of customers, and proactive market orientation, which addresses the latent needs of customers—that is, opportunities for customer value of which the customer is unaware. In the numerous market orientation–performance studies to date, the measure of market orientation has consisted virtually entirely of behaviors related to satisfying customers' expressed needs rather than satisfying their latent needs as well. The present study extends the measurement of market orientation to match the full scope of the concept—to measure both responsive market orientation and proactive market orientation. Using data from a sample of technologically diverse businesses, the present study develops a measure of proactive market orientation, refines the extant measure of responsive market orientation, and analyzes the relationship of a business's responsive and proactive market orientation to its new‐product success. The study findings imply that for any business to create and to sustain new‐product success, a responsive market orientation is not sufficient and, thus, that a proactive market orientation plays a very important positive role in a business's new‐product success. These findings make intuitive sense. For if in developing its new products a business relies solely on what customers state as their new product needs, the business is very vulnerable economically. Such a business is vulnerable not only for relying on customers' best guesses for new products, many or most of which may have little long‐term economic value for either party, but also to competitors' parallel new product responses and the inevitable resulting price competition. A business that relies solely on customers' expressed needs to develop its new products creates no new insights into value‐adding opportunities for the customer and thereby creates little or no customer dependence and foundation for customer loyalty. The important role for proactive market orientation in new‐product success is intuitively obvious—and is supported empirically in this study.     

Dynamic pricing models for ERP systems under network externality

Enterprise Resource Planning (ERP) systems vendors face great challenges to enhance their market position and maximize their profits. Being able to simultaneously predict the diffusion of an ERP and to determine the right price to charge to a customer is a complex task. Earlier work has demonstrated evidence of network effect in the diffusion of ERP software in industries. In light of this evidence, we investigate in this paper the benefit of a dynamic pricing strategy for ERP systems vendors in a business network governed by a quantitative diffusion model. Based on a real scenario in the automotive industry, those quantitative models are integrated into a simulation-based optimization approach to tackle the problem. Our findings are promising and establish the foundation of a powerful decision support tool for ERP systems vendors.     

Bidirectional Information Transfer: An Imperative for Network and Marketing Integration in a Canadian Telecommunications Firm

Market intelligence helps ensure that R&D efforts are focused on customer needs. In turn, R&D supplies the information necessary for gaining competitive advantage through advances in product and process technology. However, improved R&D–marketing integration means more than simply involving additional marketing personnel in product development. We must focus on identifying and achieving the desired level of integration. Jozée Lapierre and Brigitte Hénault present the results of a study examining the R&D–marketing interface in a large Canadian telecommunications company. Their study explores managers' perceptions of interfunctional integration during the planning and implementation of new services. The goal of this study is to identify the critical integration areas and managers' satisfaction with the organization's current level of integration. Network (i.e., technical) and marketing managers differ substantially in their perceptions of the required level of integration. However, they agree on the five most important areas of interfunctional integration: marketing involvement in establishing service development schedules; information transfer from marketing to network on competitors' moves; information transfer from marketing to network on customer requirements for new services; information transfer from network to marketing on network availability for providing evolved services; and information transfer from network to marketing on network restrictions affecting performance, after-sales servicing levels, and service pricing. In other words, network and marketing managers view information transfer between their groups as requiring the highest integration level. Both groups agree that their budgeting activities do not require as much integration as other activities. Managers from both groups are generally dissatisfied with the current level of interfunctional integration. Marketing managers are far more dissatisfied than network managers in most areas of integration explored in this study. However, network managers are more dissatisfied than their marketing colleagues in all areas involving the transfer of information from marketing to network.     

Mortgage Brokers,Origination Fees,Price Transparency and Competition

This article examines the dynamics between mortgage broker competition, origination fees and price transparency. A reverse first‐price sealed‐bid auction model is used to motivate broker pricing behavior. Confirming the model predictions, our empirical analysis shows that increased mortgage brokerage competition at the Metropolitan Statistical Area level leads to lower fees. The findings are robust to different measures of fees as well as different measures of competition. We also provide evidence that broker competition reduces mortgage origination fees on retail (nonbrokered) loans as well. In addition, our results indicate that pricing complexity is an important determinant of fees, and increased broker competition is associated with a higher probability of a loan being priced with transparency. Our results suggest that mortgage brokers increase competition and lower fees in the mortgage market.     

The computation of costs for price decisions

Business should compute costs in a particular way of pricing purposes. The correct cost computation varies with its purpose, though most executives still believe that an item has a true cost regardless of why it is computed.Even cost estimates made for price decisions will differ according to the type of price decision that is at issue. One finds important differences depending on whether one is estimating costs for a one-shot bid, for a promotional price offer that is to last for a short period, or for a decision concerning long-term price. Although the same basic principles would apply in all three cases, their application is different. The appropriate concept is that of “decision cost”, a very simple but powerful idea that leads to different cost conclusions than are reached by prevailing costing methods.     

Identifying customer behavioral factors and price premiums of green building purchasing

In recent years, global urbanization and overdevelopment have resulted in environmental degradation and an energy crisis. Promoting green buildings is among the most effective methods for achieving environmental sustainability. Although the initial costs of green buildings are higher than those of ordinary buildings, people perceive that the environmental benefits of green buildings justify their higher price premiums. From a developer's perspective, devising optimal pricing strategies according to customer-perceived prices and developers' expected profit is complex and difficult. Hence, in this study, we developed a framework based on the Howard–Sheth model of consumer behavior to identify behavioral factors that may affect consumer purchases of green buildings. An artificial neural network (ANN) was then used to develop a pricing model for predicting the price premiums of green buildings. The results revealed that the ANN model's overall prediction capability was 94%; the model's robustness was demonstrated by comparing the results produced using the model with those produced using a multiple regression analysis. In addition, the characteristics of consumers who were willing to accept higher price premiums for green buildings were identified and discussed. The proposed model can be applied as an effective decision-support tool for green building pricing and formulating marketing strategies.     

Joint pricing and inventory control for non-instantaneous deteriorating items with partial backlogging and time and price dependent demand

In this paper, a joint pricing and inventory control for non-instantaneous deteriorating items is developed. We adopt a price and time dependent demand function. Shortages is allowed and partially backlogged. The major objective is to determine the optimal selling price, the optimal replenishment schedule and the optimal order quantity simultaneously such that, the total profit is maximized. We first show that for any given selling price, optimal replenishment schedule exists and unique. Then, we show that the total profit is a concave function of price. Next, we present a simple algorithm to find the optimal solution. Finally, we solve a numerical example to illustrate the solution procedure and the algorithm.     

Centrality and pricing in spatially differentiated markets: The case of gasoline

We highlight the importance of ‘centrality’ for pricing. Firms characterized by a more central position in a spatial network are more powerful in terms of having a stronger impact on their competitors' prices and on equilibrium prices. These propositions are derived from a simple theoretical model and investigated empirically for the retail gasoline market of Vienna, Austria. We compute a measure of network centrality based on the locations of gasoline stations in the road network. Results from a spatial autoregressive model show that prices of gasoline stations are more strongly correlated with prices of central competitors.     

Editorial — Behavioral and psychological aspects of b2b pricing

In this paper we define core research questions falling within the domain of behavioral and psychological aspects of B2B pricing. We then present the papers accepted for this special issue. Central research questions are, in our view, all those instances where decisions about price violate basic principles of rational choice. Decisions about price involve two main actors. First is the customer. We are interested in how customers' purchase decisions in B2B exhibit behavioral patterns that are inconsistent with rational choice models. Second is the manager. Managers set prices and in this process are equally susceptible to violating fundamental principles of rational choice. For this special issue we have been able to accept six papers. We welcome the debate that these papers are likely to start.