Pricing Strategy and PracticeTable of Contents for Pricing Strategy and Practice. List of articles from the current issue, including Just Accepted (EarlyCite)https://www.emerald.com/insight/publication/issn/0968-4905/vol/5/iss/4?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestPricing Strategy and PracticeEmerald Publishing LimitedPricing Strategy and PracticePricing Strategy and Practicehttps://www.emerald.com/insight/proxy/containerImg?link=/resource/publication/journal/0e9c9bb3639ba35c67b2492f04a34d99/UNKNOWNhttps://www.emerald.com/insight/publication/issn/0968-4905/vol/5/iss/4?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestAnalysis of pricing strategies for new product introductionhttps://www.emerald.com/insight/content/doi/10.1108/09684909710184626/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestStates that one weakness of new product introduction (NPI) is the elapsed time required to bring the product to market. Many manufacturing companies are losing the competitive race in this area to the speedy and effective execution process, which other successful companies (for example, some Japanese electronic manufacturers) use. Analyzes two sets of companies: those that bring the products to market early; and those which do so late. Describes the advantages of a company bringing product into the marketplace before its competitors, and how a company can wrestle away a larger share of the marketplace. Also provides some closed form algorithms for computing projected shares of sales volume. Using this formula, a company can compute what sales volume a company can lock‐in by introducing a product to market when demand or need for a product is at its peak. Also provides a computational means for calculating possible loss of revenues when a company is not able to bring a product timely to the marketplace.Analysis of pricing strategies for new product introduction
Biren Prasad
Pricing Strategy and Practice, Vol. 5, No. 4, pp.132-141
States that one weakness of new product introduction (NPI) is the elapsed time required to bring the product to market. Many manufacturing companies are losing the competitive race in this area to the speedy and effective execution process, which other successful companies (for example, some Japanese electronic manufacturers) use. Analyzes two sets of companies: those that bring the products to market early; and those which do so late. Describes the advantages of a company bringing product into the marketplace before its competitors, and how a company can wrestle away a larger share of the marketplace. Also provides some closed form algorithms for computing projected shares of sales volume. Using this formula, a company can compute what sales volume a company can lock‐in by introducing a product to market when demand or need for a product is at its peak. Also provides a computational means for calculating possible loss of revenues when a company is not able to bring a product timely to the marketplace.]]>
Analysis of pricing strategies for new product introduction10.1108/09684909710184626Pricing Strategy and Practice1997-12-01© 1997 Biren PrasadPricing Strategy and Practice541997-12-0110.1108/09684909710184626https://www.emerald.com/insight/content/doi/10.1108/09684909710184626/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1997
Mode of payment and formation of reference priceshttps://www.emerald.com/insight/content/doi/10.1108/09684909710184635/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestStates that reference price has emerged as a central feature in consumer decisions. The goal of this study was to explore the contribution of mode of payment to the formulation of personal reference prices (what one believes to be a fair price for a product) and reservation prices (the highest price one is willing to pay for a product). Reference prices for the products were significantly influenced by mode of payment (check, cash, credit card). Those in the credit card condition formulated significantly higher reference and reservation prices than when other modes of payment were considered. That credit cards can raise reference prices leads to a better understanding of why consumers spend more with credit cards.Mode of payment and formation of reference prices
Jodie E. Monger, Richard A. Feinberg
Pricing Strategy and Practice, Vol. 5, No. 4, pp.142-147
States that reference price has emerged as a central feature in consumer decisions. The goal of this study was to explore the contribution of mode of payment to the formulation of personal reference prices (what one believes to be a fair price for a product) and reservation prices (the highest price one is willing to pay for a product). Reference prices for the products were significantly influenced by mode of payment (check, cash, credit card). Those in the credit card condition formulated significantly higher reference and reservation prices than when other modes of payment were considered. That credit cards can raise reference prices leads to a better understanding of why consumers spend more with credit cards.]]>
Mode of payment and formation of reference prices10.1108/09684909710184635Pricing Strategy and Practice1997-12-01© 1997 Jodie E. MongerRichard A. FeinbergPricing Strategy and Practice541997-12-0110.1108/09684909710184635https://www.emerald.com/insight/content/doi/10.1108/09684909710184635/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1997
The Filipino “tingui” retailing approach and cigarette price increasehttps://www.emerald.com/insight/content/doi/10.1108/09684909710184644/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThe practice of selling cigarettes by sticks is a phenomenon that can be observed among Asian countries. It is prevalent in urban centers where the retailing activity is one of the major economic activities undertaken by the middle and lower echelons of the social class. In a study of the switching of consumers from one brand to the other as a response to price increases, the practice has shown a bi‐directional effect. In an inter‐brand shift, it acts as a buffer slowing down the change in preference by granting the consumers an ability to buy the same brand even if the budget is not enough for one pack. The opposite, however, happens in the intra‐brand (local to foreign) shift. The practice makes it easier for the consumer to shift by lowering the perceived “sacrifice” in incremental price vis‐à‐vis the differential value between the imported and local brand.The Filipino “tingui” retailing approach and cigarette price increase
Kuang‐Jung Chen
Pricing Strategy and Practice, Vol. 5, No. 4, pp.148-155
The practice of selling cigarettes by sticks is a phenomenon that can be observed among Asian countries. It is prevalent in urban centers where the retailing activity is one of the major economic activities undertaken by the middle and lower echelons of the social class. In a study of the switching of consumers from one brand to the other as a response to price increases, the practice has shown a bi‐directional effect. In an inter‐brand shift, it acts as a buffer slowing down the change in preference by granting the consumers an ability to buy the same brand even if the budget is not enough for one pack. The opposite, however, happens in the intra‐brand (local to foreign) shift. The practice makes it easier for the consumer to shift by lowering the perceived “sacrifice” in incremental price vis‐à‐vis the differential value between the imported and local brand.]]>
The Filipino “tingui” retailing approach and cigarette price increase10.1108/09684909710184644Pricing Strategy and Practice1997-12-01© 1997 Kuang‐Jung ChenPricing Strategy and Practice541997-12-0110.1108/09684909710184644https://www.emerald.com/insight/content/doi/10.1108/09684909710184644/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1997
A cointegration analysis of demand: implications for pricinghttps://www.emerald.com/insight/content/doi/10.1108/09684909710184653/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatestThe use of modeling and statistics for the design and development of pricing strategy is prevalent in academia as well as the industry. One of the more commonly used tools by researchers and managers alike for the estimation of linear demand models is the ordinary least squares (OLS) regression. Unfortunately, a majority of data sets to which such models are applied suffer from nonstationarity ‐ that is, the dependence of a variable on its prior values ‐ thereby violating the assumptions of a basic (naïve) regression model. Estimates of variables under these conditions are known commonly to be inflated and inaccurate. While this problem is well‐known and can be corrected for among statisticians and econometricians, a simple and effective tool has not yet been designed for managers ‐ the actual users of such models. Studies some of the problems encountered when using a naïve model and proposes a simple method to check for nonstationarity and redesign the model to account for the same. Using scanner data on soup, shows that the redesigned model predicts better, fits better and offers more meaningful results. Finally, looks at the implications of estimating such models for pricing strategies and issues. Surface response analysis shows how a manager can use such models for conducting insightful studies on price sensitivity.A cointegration analysis of demand: implications for pricing
Sanjog R. Misra, Minakshi Trivedi
Pricing Strategy and Practice, Vol. 5, No. 4, pp.156-163
The use of modeling and statistics for the design and development of pricing strategy is prevalent in academia as well as the industry. One of the more commonly used tools by researchers and managers alike for the estimation of linear demand models is the ordinary least squares (OLS) regression. Unfortunately, a majority of data sets to which such models are applied suffer from nonstationarity ‐ that is, the dependence of a variable on its prior values ‐ thereby violating the assumptions of a basic (naïve) regression model. Estimates of variables under these conditions are known commonly to be inflated and inaccurate. While this problem is well‐known and can be corrected for among statisticians and econometricians, a simple and effective tool has not yet been designed for managers ‐ the actual users of such models. Studies some of the problems encountered when using a naïve model and proposes a simple method to check for nonstationarity and redesign the model to account for the same. Using scanner data on soup, shows that the redesigned model predicts better, fits better and offers more meaningful results. Finally, looks at the implications of estimating such models for pricing strategies and issues. Surface response analysis shows how a manager can use such models for conducting insightful studies on price sensitivity.]]>
A cointegration analysis of demand: implications for pricing10.1108/09684909710184653Pricing Strategy and Practice1997-12-01© 1997 Sanjog R. MisraMinakshi TrivediPricing Strategy and Practice541997-12-0110.1108/09684909710184653https://www.emerald.com/insight/content/doi/10.1108/09684909710184653/full/html?utm_source=rss&utm_medium=feed&utm_campaign=rss_journalLatest© 1997