Cenk Koçaş

Evolution of Prices in Electronic Markets Under Diffusion of Price-Comparison Shopping

Price-comparison engines allow customers to compare product offerings of online sellers and reveal almost complete information on the alternatives, and hence create erosion in store loyalty. Consequently,the competitive dynamics of online sales are affected in markets where price-comparison shopping is diffusing rapidly. We develop a dynamic competitive pricing model that deals with an asymmetric duopolistic market where the segment sizes are determined through a diffusion process. Our diffusion-of-innovations approach allows us to dynamically capture the proportion of informed and uninformed customers in a homogenous goods market. We use this model to analyze how strategic profit-maximization behavior evolves over time. This analysis shows that the increasing numbers of price-comparison shoppers pull prices down, and the rate at which prices decrease is shaped by the diffusion curve and brand preference. Our analysis shows that stores with loyal customers, or with a preference for their brands, can attain higher profits further into the diffusion process. The direct implication is that firms should use their information technology, operations, and marketing capabilities to create, enhance, and cultivate stronger preferences for, and loyalty to, their brand names to survive the inevitable information-rich markets of tomorrow.

A Model of Internet Pricing Under Price-Comparison Shopping

An empirical regularity in the price-promotion behavior of retailers of homogenous goods is explained theoretically. Based on this, a model is proposed for price competition in a market for a homogenous good with many asymmetrically positioned retailers. Asymmetry in this context refers to firms having potentially dissimilar loyal and switcher customer numbers that shape their pricing behavior in on-line markets. Incomplete information on the size of these segments results in distinguishable clusters of indistinguishable firms. To analyze these markets, a static game of price competition is developed and solved in an asymmetric oligopoly with numerous clusters of firms. The firms with the smallest ratio of switcher segment size to loyal segment size engage in fierce price competition, whereas the members of all other groups price their goods at reservation price points with no price promotions. This observation is a unique contribution and challenges the perception that all firms in markets for homogenous goods adopt mixed pricing strategies.

A system for pricing the sales distribution from blockbusters to the long tail

The long tail of retailing has been both a challenge and an opportunity for online retailers. This article provides guidelines for enhanced decision making strategies in pricing dependent on popularity, cross-sales quantity and reservation prices. Our model shows that if customer willingness to pay, or reservation price, is higher for less popular items in a category, a unique optimal price path exists which requires deep discounts on popular items. However, if the reservation price is lower for less popular items, the optimal price path is conditional on the profitability of cross-selling and the potential loss from the business of loyal customers. Analyzing data on books, songs and movies from Amazon.com, we provide empirical support for our model findings. An analysis of the same set of movies available both as instant videos and DVDs allow us control for unobserved product characteristics and yields contradictory price paths along the sales rank distribution with increasing prices for DVDs and decreasing prices for streaming movies, as predicted by our model. Display Omitted We examine the optimal discounting strategy along the sales distribution by accounting for both own and cross-sales of items and the reservation prices in the implementation of a pricing DSS.Any non-decreasing reservation price function along the sales rank distribution yields an optimal discounting strategy in which retailers price hit items lower than any non-hit item.A decreasing reservation price along the sales rank distribution coupled with a significant potential loss from loyal customers and a lack of cross-selling potential leads to hit items priced higher than non-hit items.However, a decreasing reservation price, a negligible potential loss from loyal customers and an environment conducive to cross-selling may still give way to hit items priced lower than non-hit items.We analyze data on books, MP3 songs, DVD movies and instant movies from Amazon.com and show that the same set of movies available both as instant videos and DVDs have opposing price paths along the sales rank distribution with increasing prices for DVDs and decreasing prices for streaming movies, as predicted by our model.

Finding robust timetables for project presentations of student teams

This article describes a methodology developed to find robust solutions to a novel timetabling problem encountered during a course. The problem requires grouping student teams according to diversity/homogeneity criteria and assigning the groups to time-slots for presenting their project results. In this article, we develop a mixed integer programming (MIP) formulation of the problem and then solve it with CPLEX. Rather than simply using the optimal solution reported, we obtain a set of solutions provided by the solution pool feature of the solution engine. We then map these solutions to a network, in which each solution is a node and an edge represents the distance between a pair of solutions (as measured by the number of teams assigned to a different time slot in those solutions). Using a scenario-based exact robustness measure, we test a set of metrics to determine which ones can be used to heuristically rank the solutions in terms of their robustness measure. Using seven semesters’ worth of actual data, we analyze performances of the solution approach and the metrics. The results show that by using the solution pool feature, analysts can quickly obtain a set of Pareto-optimal solutions (with objective function value and the robustness measure as the two criteria). Furthermore, two of the heuristic metrics have strong rank correlation with the robustness measure (mostly above 0.80) making them quite suitable for use in the development of new heuristic search algorithms that can improve the solution pool.

A Model of Internet Pricing Under Price Comparison Shopping: An Addendum

In “A Model of Internet Pricing Under Price Comparison Shopping,” published in this journal last year, I failed to benefit from an already existing solution to the asymmetric firm-pricing model presented by M.R. Baye, D. Kovenock, and C.G. de Vries [1]. Their paper provides a characterization of the equilibria in an oligopoly when uninformed customers do not allocate themselves equally across firms. My 2005 paper presented a characterization of the equilibria when the market is formed of asymmetric groups of symmetric firms in terms of informed as well as uninformed customers [2]. Its novel aspects included the formulation of the model with groups of firms, allowing for varying numbers of informed as well as uninformed customers across firms and validation of the model empirically.

How Trending Status and Online Ratings Affect Prices of Homogeneous Products

ABSTRACT The online retailing environment has grown more complex with the myriad information items available for customers to peruse. Two such information items include the trending lists of currently popular products, and online customer reviews and ratings of products. A trending product is one that relatively large groups of people are currently browsing, purchasing, or discussing. In this paper, we analyze the pricing implications of both types of information items. Our main goal is to test whether, acting as signals of desirability and popularity, a trending status or high ratings and reviews can lead to price cuts on homogeneous products. We provide empirical support for a model that demonstrates these relationships using data on books from twenty-four categories of Amazon.com. An important theoretical contribution of our model is that even in the absence of strategic considerations or demand dependencies, our model suggests lower prices for trending and positively reviewed products. Our work shows that pricing systems using popularity and average customer ratings as inputs can help achieve increased profitability.