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on Marketing |
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Issue of 2010‒02‒27
four papers chosen by Joao Carlos Correia Leitao University of Beira Interior and Technical University of Lisbon |
| By: | Griffith, R.; Leibtag, E.; Leicester, A.; Nevo, A. |
| Abstract: | This paper documents the potential and actual savings that consumers realize from four particular types of purchasing behavior: purchasing on sale; buying in bulk (at a lower per unit price); buying generic brands; and choosing outlets. How much can and do households save through each of these behaviors? How do these patterns vary with consumer demographics? We use data collected by a marketing firm on all food purchases brought into the home for a large, nationally representative sample of U.K. households in 2006. We are interested in how consumer choice affects the measurement of price changes. In particular, a standard price index based on a fixed basket of goods will overstate the rise in the true cost of living because it does not properly consider sales and bulk purchasing. According to our measures, the extent of this bias might be of the same or even greater magnitude than the better-known substitution and outlet biases. |
| Date: | 2009–03 |
| URL: | http://d.repec.org/n?u=RePEc:ner:ucllon:http://eprints.ucl.ac.uk/18798/&r=mkt |
| By: | Bansal, Sangeeta; Gruère, Guillaume |
| Abstract: | In 2006, India proposed a draft rule requiring the labeling of all genetically modified (GM) foods and products derived thereof. In this paper, we use primary and secondary market data to assess the economic implications of introducing such a mandatory labeling policy for GM food. We focus on four products that would likely be the first affected by such a regulation in India: cottonseed oil, soybean oil, brinjal (eggplant), and rice. We find that GM food labeling would generate a specific market outcome for each of these products. With GM labeling, virtually all cottonseed oil would be labeled as GM, with limited costs for all actors involved, but also limited benefit for consumers. Labeling soybean oil derived from GM crops could affect market shares for edible oils at the benefit of domestic oils, and non-GM soybean oil could appear on the market at a very limited scale. Labeling GM brinjal would be extremely challenging. Assuming it was implemented, some non-GM brinjal would be sold at a premium in high-income retail outlets, while virtually all others would be labeled GM. A similar outcome would occur for rice, with high-quality rice used for both domestic consumption and exports markets certified non-GM and most of the remaining rice labeled as GM. In each of the cases, labeling would generate significant adjustment costs for the industry and large enforcement costs, and consumer benefit would not always be visible and would highly depend on the degree of enforcement. In fact, voluntary labeling could achieve less-distorted results with lower costs and therefore appears to be a superior regulatory solution. Still, provided enforcement is ensured, a well-designed mandatory labeling regulation with limited product coverage, a non-zero labeling threshold, and an informative labeling content would lead to a much better outcome and lower costs in India than the current draft rule, especially if it is accompanied by a large awareness campaign regarding GM food and consumer safety in India. |
| Keywords: | Genetically modified food, Labeling, market shares, domestic consumption, soybean oil, export markets, rice, cottonseed oil, enforcement costs, consumer safety, Food marketing, Genetic resources, |
| Date: | 2010 |
| URL: | http://d.repec.org/n?u=RePEc:fpr:ifprid:946&r=mkt |
| By: | Koji Miyawaki (National Institute for Environmental Studies); Yasuhiro Omori (Faculty of Economics, University of Tokyo); Akira Hibiki (National Institute for Environmental Studies) |
| Abstract: | Block rate pricing is often applied to income taxation, telecommunication services, and brand marketing in addition to its best-known application in public utility services. Under block rate pricing, consumers face piecewise-linear budget constraints. A discrete/ continuous choice approach is usually used to account for piecewise-linear budget constraints for demand and price endogeneity. A recent study proposed a methodology to incorporate a separability condition that previous studies ignore, by implementing a Markov chain Monte Carlo simulation based on a hierarchical Bayesian approach. To extend this approach to panel data, our study proposes a Bayesian hierarchical model incorporating the individual effect. The random coefficients model result shows that the price and income elasticities are estimated to be negative and positive, respectively, and the coefficients of the number of members and the number of rooms per household are estimated to be positive. Furthermore, the AR(1) error component model suggests that the Japanese residential water demand does not have serial correlation. |
| Date: | 2010–02 |
| URL: | http://d.repec.org/n?u=RePEc:tky:fseres:2010cf717&r=mkt |
| By: | Glady, Nicolas; Baesens, Bart; Croux, Christophe |
| Abstract: | The definition and modeling of customer loyalty have been central issues in customer relationship management since many years. Recent papers propose solutions to detect customers that are becoming less loyal, also called churners. The churner status is then defined as a function of the volume of commercial transactions. In the context of a Belgian retail financial service company, our first contribution is to redefine the notion of customer loyalty by considering it from a customer-centric viewpoint instead of a productcentric one. We hereby use the customer lifetime value (CLV) defined as the discounted value of future marginal earnings, based on the customer's activity. Hence, a churner is defined as someone whose CLV, thus the related marginal profit, is decreasing. As a second contribution, the loss incurred by the CLV decrease is used to appraise the cost to misclassify a customer by introducing a new loss function. In the empirical study, we compare the accuracy of various classification techniques commonly used in the domain of churn prediction, including two cost-sensitive classifiers. Our final conclusion is that since profit is what really matters in a commercial environment, standard statistical accuracy measures for prediction need to be revised and a more profit oriented focus may be desirable. |
| Keywords: | Data mining; Decision support systems; Marketing; Churn prediction; |
| Date: | 2009–08 |
| URL: | http://d.repec.org/n?u=RePEc:ner:leuven:urn:hdl:123456789/201349&r=mkt |