Static Pricing Problems under Mixed Multinomial Logit Demand

Price differentiation is a common strategy for many transport operators. In this paper, we study a static multiproduct price optimization problem with demand given by a continuous mixed multinomial logit model. To solve this new problem, we design an efficient iterative optimization algorithm that asymptotically converges to the optimal solution. To this end, a linear optimization (LO) problem is formulated, based on the trust-region approach, to find a "good" feasible solution and approximate the problem from below. Another LO problem is designed using piecewise linear relaxations to approximate the optimization problem from above. Then, we develop a new branching method to tighten the optimality gap. Numerical experiments show the effectiveness of our method on a published, non-trivial, parking choice model

Econometric Analysis of Pricing and Operational Strategies

This dissertation contains three essays. The first essay, entitled Pricing and Production Flexibility: An Empirical Analysis of the U.S. Automotive Industry, uses a detailed dataset of the U.S. auto industry to examine the relationship between production flexibility and responsive pricing. Our analysis shows that deploying production flexibility is associated with a reduction in observed discounts and with an increase in plant utilization. Our results allow quantifying some of the benefits of production flexibility. The second essay, entitled An Empirical Analysis of Reputation in Online Service Marketplaces, uses a detailed dataset from a leading online intermediary for software development services to empirically examine the role of reputation on choices and prices in service marketplaces. We find that buyers trade off reputation and price and are willing to accept higher bids posted by more reputable bidders. Sellers primarily use a superior reputation to increase their probability of being selected, as opposed to increasing their prices. Our analysis shows that the numerical reputation score has a smaller effect in situations where there exists a previous relationship between buyer and seller, when the seller has certified his or her skills, when the seller is local, or in situations that prompt higher interpersonal trust. The third essay, entitled The Effects of Product Line Breadth: Evidence from the Automotive Industry, studies the effects of product line breadth on market shares and costs, using data from the U.S. automotive industry. Our results show a positive association between product line breadth and market share and production costs. Beyond the effects on production costs, we study the effect of product line breadth on mismatch costs, which arise from demand uncertainty, and we find that product line breadth has a substantial impact on average discounts and inventories. Our results also show that platform strategies can reduce production costs and that a broader product line can provide a hedge against changes in demand conditions

Why to design modular products?

This paper is based on the development project of productivity by applying principles of product modularity and design reuse. The focus is on companies operating in manufacturing industry and specializing in large investment project deliveries. Analyzing the business impact of modularity is one method and tool used in modularization projects. The analysis is made to ensure that the investment in the development of modular products and the supporting way to operate is justified and supports the company's strategic business objectives. Preliminary business impact analyzes are usually carried out before the actual technical modularization project starts to justify starting the project. Analyzes are made also during the modularization project at different stages, for example to compare alternative concepts or module partitioning types. To support the business impact analysis of modularization, several possible benefits and value creation mechanisms have been identified in previous publications. These mechanisms can be linked to many stages of the product life cycle. This paper first reviews the main mechanisms of modularization through a literature review. In addition to this, based on an ongoing modularization project in a case study with investment product deliveries, we present as new information the latest findings on different potential benefits of modularization to reinforce the previous literature.publishedVersionPeer reviewe

Approximation algorithms for product framing and pricing

We propose one of the first models of “product framing” and pricing. Product framing refers to the way consumer choice is influenced by how the products are framed or displayed. We present a model in which a set of products is displayed or framed into a set of virtual web pages. We assume that consumers consider only products in the top pages with different consumers willing to see different numbers of pages. Consumers select a product, if any, from these pages following a general choice model. We show that the product-framing problem is NP-hard. We derive algorithms with guaranteed performance relative to an optimal algorithm under reasonable assumptions. Our algorithms are fast and easy to implement. We also present structural results and design algorithms for pricing under framing effects for the multinomial logit model. We show that, for profit maximization problems, at optimality, products are displayed in descending order of their value gap and in ascending order of their markups

Manufacturing System and Supply Chain Analyses Related to Product Complexity and Sequenced Parts Delivery

Mixed model assembly has been widely used in many industries. It is applied in order to effectively deal with increasing product complexity. Sequencing and resequencing on a mixed-model assembly line is also complicated by high product complexity. To improve the performance of a mixed-model assembly system and the supply chain, one can develop efficient sequencing rules to address sequencing problems, and manage product complexity to reduce its negative impact on the production system. This research addresses aspects of sequence alteration and restoration on a mixed-model assembly line for the purpose of improving the performance of a manufacturing system and its supply chain, and addresses product complexity analysis. This dissertation is organized into Parts 1, 2, and 3 based on three submitted journal papers. Part 1. On a mixed-model assembly line, sequence alteration is generally used to intentionally change the sequence to the one desired by the downstream department; and sequence restoration is generally applied to achieve sequence compliance by restoring to the original sequence that has been unintentionally changed due to unexpected reasons such as rework. Rules and methods for sequence alteration using shuffling lines or sorting lines were developed to accommodate the sequence considerations of the downstream department. A spare units system based on queuing analysis was proposed to restore the unintentionally altered sequence in order to facilitate sequenced parts delivery. A queuing model for the repairs of defective units in the spare units system was developed to estimate the number of spare units needed in this system. Part 2. Research was conducted on product complexity analysis. Data envelopment analysis (DEA) was first applied to compare product complexity related to product variety among similar products in the same market, two DEA models including their respective illustrative models considering various product complexity factors and different comparison objectives were developed. One of these models compared the product complexity factors in conjunction with sales volume. The third DEA model was developed to identify product complexity reduction opportunities by ranking various product attributes. A further incremental economic analysis considering the changes in costs and market impact by an intended complexity change was presented in order to justify a product complexity reduction opportunity identified by the DEA model. Part 3. Two extended DEA models were developed to compare the relative complexity levels of similar products specifically in automobile manufacturing companies. Some automobile product attributes that have significant cost impact on manufacturing and the supply chain were considered as inputs in the two extended DEA models. An incremental cost estimation approach was developed to estimate the specific cost change in various categories of production activities associated with a product complexity change. A computational tool was developed to accomplish the cost estimation. In each of the above stated parts, a case study was included to demonstrate how these developed rules, models, or methods could be applied at an automobile assembly plant. These case studies showed that the methodologies developed in this research were useful for better managing mixed-model assembly and product complexity in an automobile manufacturing system and supply chain

PRODUCT VARIETY, SERVICE VARIETY, AND THEIR IMPACT ON DISTRIBUTORS

Despite considerable research relating to product variety, few studies have analyzed the impact of product variety on distributors. Furthermore, compared to research on product variety, service variety has been overlooked in the literature. This dissertation consists of three essays: Essay One examines the direct effect of product variety on sales, its indirect effect on sales through stockouts, as well as the total impact of product variety on sales performance. Essay Two develops a moderated mediation model to investigate how service quality and market performance are affected by service variety and the interaction impacts of different types of services. Essay Three analyzes a dynamic system, which includes influences of product and service variety on demand and costs and their reverse impacts on variety decisions

Optimal and competitive assortments with endogenous pricing under hierarchical consumer choice models’,

T his paper studies assortment planning and pricing for a product category with heterogeneous product types from two brands. We model consumer choice using the nested multinomial logit framework with two different hierarchical structures: a brand-primary model in which consumers choose a brand first, then a product type in the chosen brand, and a type-primary model in which consumers choose a product type first, then a brand within that product type. We consider a centralized regime that finds the optimal solution for the whole category and a decentralized regime that finds a competitive equilibrium between two brands. We find that optimal and competitive assortments and prices have quite distinctive properties across different models. Specifically, with the brand-primary model, both the optimal and the competitive assortments for each brand consist of the most popular product types from the brand. With the type-primary choice model, the optimal and the competitive assortments for each brand may not always consist of the most popular product types of the brand. Instead, the overall assortment in the category consists of a set of most popular product types. The price of a product under the centralized regime can be characterized by a sum of a markup that is constant across all products and brands, its procurement cost, and its marginal operational cost, implying a lower price for more popular products. The markup may be different for each brand and product type under the decentralized regime, implying a higher price for brands with a larger market share. These properties of the assortments and prices can be used as effective guidelines for managers to identify and price the best assortments and to rule out nonoptimal assortments. Our results suggest that to offer the right set of products and prices, category and/or brand managers should create an assortment planning process that is aligned with the hierarchical choice process consumers commonly follow to make purchasing decisions