Consumer environmental awareness and competition in two-stage supply chains

This paper focuses on the impact of competition and consumers’ environmental awareness on key supply chain players. We consider both the production competition between partially substitutable products made by different manufacturers, and the competition between retail stores. We use two-stage Stackelberg game models to investigate the dynamics between the supply chain players given three supply chain network structures. We find that as consumers’ environmental awareness increases, retailers and manufacturers with superior eco-friendly operations will benefit; while the profitability of the inferior eco-friendly firm will tend to increase if the production competition level is low, and will tend to decrease if the production competition level is high. In addition, higher levels of retail competition may make manufacturers with inferior eco-friendly operations more likely to benefit from the increase of consumers’ environmental awareness. Moreover, as production competition intensifies, the profits of the retailers will always increase, while the profits of the manufacturers with inferior eco-friendly operations will always decrease. The profitability of the manufacturers with superior eco-friendly operations will also tend to decrease, unless consumers’ environmental awareness is high and the superior manufacturer has a significant cost advantage related to product environmental improvement.     

Using MSRP to enhance the ability of rebates to control distribution channels

Manufacturers have increasingly instituted widespread mail-in rebate programs in recent years. Two primary purposes for rebates are to: (1) more directly impact consumer demand by reducing net retail price, and (2) capitalize on consumers’ slippage behavior because not all consumers who intend to redeem the rebate at purchase time end up actually redeeming it. However, retailers can counteract the power of rebates to impact demand by simply raising the retail price by the amount of the manufacturer’s rebate. We show that by combining a manufacturer’s suggested retail price (MSRP) along with a rebate, the manufacturer can better control the channel by inhibiting the retailer’s ability to raise price, particularly when consumers exhibit loss aversion. As a result, incorporating MSRP with a rebate promotion plan increases the manufacturer’s profit. More surprisingly, the profit of the supply chain as a whole also increases, and the channel efficiency increases as well. In fact, contrary to results from the existing rebate literature suggesting that rebates should always be offered whenever slippage exists, we demonstrate that MSRP can actually be a more effective tool than rebates in managing retailer and consumer behavior when consumers do not have sufficient loss aversion and the slippage rate is low enough.     

Stochastic diffusion models with advertising and word-of-mouth effects

This paper presents a stochastic diffusion model which incorporates advertising word-of-mouth effects. The model defines a 3 variate stochastic process based on explicit assumptions regarding consumer behavior and consumers' response to advertising. The model generalizes a wide variety of advertising models and in addition includes several classes of consumers, interaction effects between these consumers and, of course, a stochastic framework that may be used for assessing the risk implications of advertising policies and for empirical analyses purposes.     

Optimization and analysis of the profitability of tariff structures with two-part tariffs

Service providers often offer tariff structures with several two-part tariffs that consist of a fixed fee and a usage price, such that consumers may pick the tariff they prefer. Prices of tariffs have significant impacts on service providers’ profit, because they simultaneously influence consumers’ tariff choices and their usage. The number of tariffs also plays an important role, because more tariffs segment the market better but also increase the administrative burden and require more marketing effort. This article presents a mixed-integer nonlinear programming optimization problem to determine profit-maximizing tariffs; compares several heuristic search methods, in particular, the gradient method, stochastic search, and simulated annealing, to solve this problem; analyses the profitability of different tariff structures; and outlines the factors that drive differences in profitability across various tariff structures. The results show that especially for large samples of more than 100 consumers, simulated annealing performs best and deviates only 0.2% from the optimum. Structures with fewer two-part tariffs are generally sufficient, because additional two-part tariffs only negligibly increase service providers’ profit.     

Pricing and effort investment for a newsvendor-type product

We investigate a dominant retailer’s optimal joint strategy of pricing and timing of effort investment and analyze how it influences the decision of the manufacturer, the total supply chain profit, and the consumers’ payoff. We consider two pricing schemes of the retailer, namely, dollar markup and percentage markup, and two effort-investment sequences, namely, ex-ante and ex-post. A combination of four cases is analyzed. Our results show that: (1) under the same effort-decision sequence, a percentage-markup pricing scheme leads to higher expected profit for the retailer and the whole supply chain, but a lower expected profit for the manufacturer and a higher retail price for the consumers; (2) under the same markup-pricing strategy, the dominant retailer always prefers to postpone her effort decision until the manufacturer makes a commitment to wholesale price, since it can result in a Pareto-improvement for all the supply chain members. That is, the retailer’s and manufacturer’s expected profits are higher and the consumers pay a lower retail price; and (3) among the four joint strategies, the dominant retailer always prefers the joint strategy of percentage-markup plus ex-post effort decision. However, the dominated manufacturer always prefers the joint strategy of dollar-markup plus ex-post effort decision, which is also beneficial to the end consumers.     

Robust equilibria in location games

In the framework of spatial competition, two or more players strategically choose a location in order to attract consumers. It is assumed standardly that consumers with the same favorite location fully agree on the ranking of all possible locations. To investigate the necessity of this questionable and restrictive assumption, we model heterogeneity in consumers’ distance perceptions by individual edge lengths of a given graph. A profile of location choices is called a “robust equilibrium” if it is a Nash equilibrium in several games which differ only by the consumers’ perceptions of distances. For a finite number of players and any distribution of consumers, we provide a complete characterization of robust equilibria and derive structural conditions for their existence. Furthermore, we discuss whether the classical observations of minimal differentiation and inefficiency are robust phenomena. Thereby, we find strong support for an old conjecture that in equilibrium firms form local clusters.     

QoS commitment between vertically integrated autonomous systems

Vertically integrated autonomous systems bargain to provide quality of service guarantees and revenue sharing. Depending on the perceived quality of service and access price, consumers determine whether they subscribe to the access provider’s service. Four types of contracts are compared: (i) best effort, (ii) bilateral bargaining, (iii) cascade negotiations and (iv) grand coalition cooperation; the impact of the consumers’ QoS sensitivity parameter and power relation are tested for each contract. Assuming that the consumers’ quality of service sensitivity parameter is unknown and might evolve dynamically due to error judgement, word-of-mouth effect or competition pressure, a learning algorithm is detailed and implemented by each integrated autonomous systems under asymmetrical information. Its convergence and the influence of bias introduction by the most informed autonomous system is analyzed.     

Average shadow price and equilibrium price: A case study of tradable pollution permit markets

Shadow prices indicate implicit values of limited resources at the margin and provide important information in decision making for resource management. In continuous economic models, shadow prices associated with demand-supply balance constraints represent consumers’ willingness to pay and producers’ marginal cost, hence they correspond to market equilibrium prices. As well known, however, marginal analysis fails in the case of discrete optimization, such as mixed integer programming. An alternative concept has been introduced in the literature to measure the value of an extra unit of a limited resource in such cases. This concept is based on average rather than marginal values, thus called the average shadow price, and interpreted in the same way as conventional shadow prices. Whether average shadow prices in a discrete economic model can serve as market equilibrium prices has not been addressed in the related literature. The present paper addresses this issue in an empirical setting. Using a tradable pollution permit market as an example, where firms’ YES/NO type technology adoption decisions are represented by binary variables, we show that the average shadow price of tradable permits can be interpreted as the equilibrium price only when certain conditions related to the cost structure and emission levels hold. On the other hand, we show that an iterative procedure based on individual firms’ cost minimizing behavior presents a better approach for finding a price that can eliminate or reduce the gap between demand and supply of permits in the market.     

Dynamic pricing of multiple home delivery options

Online grocers accept delivery bookings and have to deliver groceries to consumers’ residences. Grocery stores operate on very thin margins. Therefore, a critical question that an online grocery store needs to address is the cost of home delivery operations. In this paper, we develop a Markov decision process-based pricing model that recognizes the need to balance utilization of delivery capacity by the grocer and the need to have the goods delivered at the most convenient time for the customer. The model dynamically adjusts delivery prices as customers arrive and make choices. The optimal prices have the following properties. First, the optimal prices are such that the online grocer gains the same expected payoff in the remaining booking horizon, regardless of the delivery option independently chosen by a consumer. Second, with unit order sizes, delivery prices can increase due to dynamic substitution effects as there is less time left in the booking horizon.     

Privacy and pricing personal information

The issues we address here are – How should a firm (e.g. Internet service provider (ISP)) that is capable of collecting personal information (browsing information, purchase history, etc.) about consumers, price its service, given that consumers vary in their valuation for privacy, and also vary in terms of the value of their personal information to a third party (firms that need consumer information)? Should the firm have a blanket policy of never collecting, or a policy of always collecting and revealing information? Surprisingly we find that in some cases the collector of information may be no worse off in the asymmetric information case than in the full information case. The paper provides a justification for the strategy of some firms such as ISP’s which never collect information and also for the strategy of other firms, like grocery stores that do. We also find that it is non-optimal for the firm to design contracts where the consumer can choose an intermediate level of privacy.     

Mathematical programming models for revenue management under customer choice

We study a network airline revenue management problem with discrete customer choice behavior. We discuss a choice model based on the concept of preference orders, in which customers can be grouped according to a list of options in decreasing order of preference. If a customer’s preferred option is not available, the customer moves to the next choice on the list with some probability. If that option is not available, the customer moves to the third choice on the list with some probability, and so forth until either the customer has no other choice but to leave or his/her request is accepted. Using this choice model as an input, we propose some mathematical programs to determine seat allocations. We also propose a post-optimization heuristic to refine the allocation suggested by the optimization model. Simulation results are presented to illustrate the effectiveness of our method, including comparisons with other models.     

Assortment optimization under a multinomial logit model with position bias and social influence

Motivated by applications in retail, online advertising, and cultural markets, this paper studies the problem of finding an optimal assortment and positioning of products subject to a capacity constraint in a setting where consumers preferences can be modeled as a discrete choice under a multinomial logit model that captures the intrinsic product appeal, position biases, and social influence. For the static problem, we prove that the optimal assortment and positioning can be found in polynomial time. This is despite the fact that adding a product to the assortment may increase the probability of selecting the no-choice option, a phenomenon not observed in almost all models studied in the literature. We then consider the dynamics of such a market, where consumers are influenced by the aggregate past purchases. In this dynamic setting, we provide a small example to show that the natural and often used policy known as popularity ranking, that ranks products in decreasing order of the number of purchases, can reduce the expected profit as times goes by. We then prove that a greedy policy that applies the static optimal assortment and positioning at each period, always benefits from the popularity signal and outperforms any policy where consumers cannot observe the number of past purchases (in expectation).     

Customization competition between branded firms: Continuous extension of product line from core product

We study a competition of product customization between two branded firms by a game-theoretic approach. Firms produce products with two attributes: one attribute indicates a characteristic with regard to “function” or “design” of a product and the other indicates “taste” or “flavor” of the product, which reflects consumers’ brand/taste preferences. Two branded firms have their own specific core products and our customization is defined as a continuous extension of their product line from the core product only along the “function” attribute. In particular, we allow asymmetric positions of core products, which may create the position advantage/disadvantage between firms. We suppose that consumers incur their selection costs with regard to finding their most favorable item among a rich variety of products and firms incur their customizing costs with regard to extending their product lines. We first show that in the equilibrium, branded firms should fundamentally adopt their customizations to cover the center space in the market as far as possible, regardless of the position of the competitor’s core product. Therefore, the position of the core product contributes to the creation of a competitive advantage: when one firm’s core product is located more closely to the center of the market than the competitor’s, its customization can always cover more range of the center space in the market, while keeping its degree of customization smaller than the competitor’s. Furthermore, we show some implications of unit-cost improvement: in a short run, a firm is better off concentrating on the improvement of the unit selection cost rather than the unit customizing cost. In contrast, in a long run, both firms can benefit from the improvement of the unit customizing cost.     

Full-line or specialization strategy? The negative effect of product variety on product line strategy

This paper studies the product line decisions of firms under two consumer segments differing in their quality-sensitivity. We focus on a negative impact of the product variety on the consumers’ motivation to purchase, while each product is horizontally differentiated. In the presence of this impact and high fixed costs relative to variable costs, it is shown that when a highly quality-sensitive segment exists, it is always advantageous for the monopoly to specialize in only one product serving this segment. However, the appearance of a competitor can drastically change the product line in the market. Under the duopolistic setting where two firms sequentially determine their product lines, we show that the leader gains a better financial result by offering its product to the low segment for many cases, including the case where no product is offered to the high segment by either of the firms who are in equilibrium. Furthermore, we obtain another interesting result that indicates that the follower’s profit can exceed the leader’s profit when the quality-sensitivities between the two consumer segments are sufficiently different, even though the two firms are symmetric except for the order of their product offerings.     

A note on price and quality competition between asymmetric firms

This paper analyzes the impact of asymmetry between firms on the outcome of price and quality competition from a microeconomic viewpoint. Consumers purchase a product based on not only its price but also its quality level; therefore, two firms compete in determining their prices and quality levels to maximize their profits. The asymmetry arises from the difference in consumers’ loyalty to each firm; that asymmetry then determines a character of differentiation between firms. Our purpose is to show how asymmetry influences competition under varying consumers’ price- and quality-sensitivity. In doing so, we extend earlier work in the area of price and quality competition. We show that in both the moderately quality-sensitive and price-sensitive markets, higher consumers’ sensitivity as well as lower consumers’ loyalty to any firm leads to intense competition, resulting in a decrease of both firms’ equilibrium profits. On the other hand, in highly quality-sensitive market, asymmetry compels the smaller firm to change its competitive strategy. In general, this is more beneficial to the larger firm, as the smaller firm’s profit tends to decline. In the worst case, the smaller firm is driven out of business under equilibrium.     

Analysis of the effectiveness of manufacturer-sponsored retailer gift cards in supply chains

Some manufacturers sponsor “free” retailer gift cards to be given to consumers who purchase their products. These gift cards are paid for by the manufacturer and are redeemable on all products at the retailer. We develop a model of such a supply chain. We analyze cases in which the gift cards’ redemption rate is constant or increasing in gift card value. The results indicate that in addition to the redemption rate and consumers’ valuation for gift card dollars, the profitability of manufacturer-sponsored gift cards depends on the average gross margin of the retailer and the type of purchases consumers make with gift cards. Furthermore, we show that under certain conditions, free gift cards will increase the expected profits of the retailer and manufacturer as well as decrease the retail price of the product. These conditions include a retailer with large average gross margin and consumers using gift cards to purchase products they would not buy with cash otherwise. Furthermore, all consumers, including those who do not redeem the gift card, are more likely to benefit from a reduced retail price when their probability of redeeming the gift card after purchase is equal to their estimated redemption probability at purchase time. We show the conditions under which gift cards are more profitable than cash mail-in rebates. We develop an incentive scheme to improve the performance of supply chains with gift cards.     

Supply chain structure in a market with deceptive counterfeits

Deceptive counterfeits differ from non-deceptive ones in that they are packaged and sold as authentic brand name products so that consumers may buy counterfeits unknowingly. When a distribution channel, referred to as the general channel, has been penetrated with deceptive counterfeits, a brand name company may need to restructure the way its products are distributed and rely on reliable channels such as certified stores or manufacturer-owned stores to guarantee 100% authenticity. In this paper, we first identify the conditions under which the general channel will carry deceptive counterfeits, and then analyze the optimal supply chain structure in the presence of counterfeits as well as by incorporating the wholesale price decisions, consumers’ risk attitude towards counterfeits and consumer loyalty towards the reliable stores. Our main finding is that the brand name company should continue to sell, sometimes exclusively, through the general channel despite deceptive counterfeiting under various conditions.     

Price and quality competition: The effect of differentiation and vertical integration

This paper studies an instance of price and quality competition between firms as seen in the recent Internet market. Consumers purchase a product based on not only its price but also its quality level; therefore, two firms compete in determining their prices and quality levels to maximize their profits. Characterizing this competition from a microeconomic viewpoint, we consider two possible business strategies that firms can utilize to overcome the competition—the differentiation and the vertical integration with another complementary firm. We show an interesting result not seen in the well-known Bertrand price competition: not only does the differentiation always increase the firms’ profits, but also it can increase the consumer’s welfare in a quality-sensitive market. We further derive that under some mild conditions the monopolistic vertical integration that excludes the combination-purchase with a competitor’s product is beneficial for both the integrated firm and its consumers.     

Genetic algorithms for portfolio selection problems with minimum transaction lots

Conventionally, portfolio selection problems are solved with quadratic or linear programming models. However, the solutions obtained by these methods are in real numbers and difficult to implement because each asset usually has its minimum transaction lot. Methods considering minimum transaction lots were developed based on some linear portfolio optimization models. However, no study has ever investigated the minimum transaction lot problem in portfolio optimization based on Markowitz’ model, which is probably the most well-known and widely used. Based on Markowitz’ model, this study presents three possible models for portfolio selection problems with minimum transaction lots, and devises corresponding genetic algorithms to obtain the solutions. The results of the empirical study show that the portfolios obtained using the proposed algorithms are very close to the efficient frontier, indicating that the proposed method can obtain near optimal and also practically feasible solutions to the portfolio selection problem in an acceptable short time. One model that is based on a fuzzy multi-objective decision-making approach is highly recommended because of its adaptability and simplicity.     

Multistage optimization of option portfolio using higher order coherent risk measures

Choosing a suitable risk measure to optimize an option portfolio’s performance represents a significant challenge. This paper is concerned with illustrating the advantages of Higher order coherent risk measures to evaluate option risk’s evolution. It discusses the detailed implementation of the resulting dynamic risk optimization problem using stochastic programming. We propose an algorithmic procedure to optimize an option portfolio based on minimization of conditional higher order coherent risk measures. Illustrative examples demonstrate some advantages in the performance of the portfolio’s levels when higher order coherent risk measures are used in the risk optimization criterion.