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We study how price dispersion varies with product characteristics at a popular online price comparison site – Shopper.com. Our primary finding suggests that price dispersion in online markets varies with product characteristics and firm behavior. We also find evidence that the level of dispersion varies with the percent of firms listing price information in multiple categories. When the percent of firms listing prices in multiple categories is relatively high (low), price dispersion is low (high).

The objective of this study is to analyze price dispersion in the context of internet based shopping malls and assess which of the main informational elements available online about sellers affect online price dispersion.

The author collected data for 100 models of watches from seven major brands and 100 models of cameras from nine major brands available for sale on Amazon. Statistical regression of price dispersion against average price, number of stores, shipping charge variation, average number of customer reviews, variation in the percentage of positive reviews and a dummy variable of product type were performed.

It is shown that price dispersion is present even in an online shopping mall. The conclusion significantly adds to the online pricing research, by showing that price dispersion is influenced by the average product price and product type and shipping charges. The number of stores does not affect price dispersion because there is no obstacle impeding the customer from finding the prices for all stores. A key finding is that the number of customer reviews significantly influences online price dispersion.

The study only analyzes price dispersion for two products using secondary data. Future studies can analyze different types of goods and focus on which elements affect the buyers' store selection by using primary data.

Managers can see that there are numerous other elements of information besides price that influence buying decisions. Practitioners need to note the importance of customer reviews in online settings, including the significance of the number of reviews as signal of experience and reliability.

The paper shows that online price dispersion exists even in the context of practically inexistent search costs. Even though the buyers have instant access to all prices of a product, they use a combination of elements in order to decide the seller selection. A key contribution of the study shows that the amount of information available about the seller and the customer reviews significantly influence online price dispersion.

The purpose of this study is to find the role of online informediaries on the perspective of price comparison and information aggregator. Specifically, the author wants to explain how the level of product involvement moderates the effect of price dispersion and product information quality on attitude toward product in online informediaries.

The data for this study are obtained from a three‐way factorial experimental research design. Data were collected from 258 college students who have an experience with an online informediary. Combining ANCOVA and regression analysis enables the study of attitude formation and yields encouraging results.

The study finds that high‐involvement consumers focus on systematic cues (e.g. product attributes) in evaluating product quality. However, when they feel that their initial search yields insufficient results, causing them to perceive more product performance risk, they search for additional cues (e.g. price dispersion). Low‐involvement consumers are mainly affected by price dispersion, which is a heuristic cue, and they evaluate the product more favorably under a high (vs low) level of price dispersion.

This paper is one of the first to consider and empirically test a heuristic‐systematic model for attitude toward product in online informediaries. It also uniquely tests the level of price dispersion to discern the important motivating factors.

This paper provides a comprehensive analysis of online price dispersion in Europe, across a broad range of product categories and countries. Using the dominant European price comparison site we collected firm specific prices, weekly, from seven European countries (Denmark, France, Italy, Netherlands, Spain, Sweden and the United Kingdom) for 31 unique products, falling into five distinct product categories (printers, PDAs, scanners, games consoles, computer games and music), over the nine-month period October 2001 to June 2002. The resulting data set comprises over 17,000 individual price observations.

Using a number of alternative measures of price dispersion we find significant differences in the degree of price dispersion observed in online markets, both between countries and across product categories. We consider alternative explanations for online price dispersion and analyze their significance in explaining the observed differences.

We investigate how online price dispersion has evolved since the bursting of the Internet bubble by comparing price dispersion levels in years 2000, 2001, and 2003 and between multi-channel and pure play e-tailers. The results show that although online price dispersion declined between 2000 and 2001 when there was a shakeout in Internet retailing, it increased from 2001 to 2003, the post bubble period, in particular, for desktop computers, laptop computers, PDAs, electronics and software. The proportion of items for which price dispersion at multi-channel retailers was higher than that at pure play e-tailers, increased steadily during 2000–2003. These findings suggest that online price dispersion is persistent even as Internet markets mature.

The purpose of this research is to take into consideration the country effect in online and offline environments and compares price levels and dispersion online v. offline across the two largest Continental European markets, thus adding a new dimension in price comparisons and multichannel pricing strategies.

Based on an empirical analysis of data collected in one product category (CDs), our findings for France and Germany show that price levels ‐including shipping costs – are always higher online than offline in each country and price dispersion is persistent across markets. Calculating mean prices for the two countries, ANOVA tests reveal significant differences among the two sets of data. Using standard deviation as the measurement for price dispersion, Levene statistics reveal a higher degree of online price dispersion than offline and statistically significant differences between the two sample countries.

Even if our approach need to be extended to more product categories and more countries, our article may be interesting for practitioners, policy makers and managers. It clearly shows that the “frictionless capitalism and cost transparency hypothesis” has proven to be wrong most of the time even if many retailers still believe they must sacrifice the possibility of pricing up when they go on the internet. As demonstrated by our findings, retailers can take advantage of online relative indifference to price to capture some margin premium and enjoy excellent results.

Our results also demonstrate that, even if results show some similarities and common trends, differences among France and Germany still remain important. As a consequence, marketers should continue to approach the European marketplace with full awareness of its diversity.

One main concern regarding the use of reference prices in advertisements relates to the possibility of deception due to consumers' positive response towards exaggerated or implausible claims. This paper examines the moderating roles of a contextual variable‐market price dispersion for a product category, and that of an individual level variable‐need for cognition, in influencing consumer evaluation of reference prices across two experiments. The results support the hypothesized effects of need for cognition and demonstrate that, for low need, for cognition individuals, increasing the level of reference price results in positive effects on value perception and shopping intention.

Cross-border e-commerce in China has been booming in recent years. This paper aims to study pricing in Chinese cross-border e-commerce companies and focuses on the baby food market, which is simply examined as a case study to highlight broader implications. In this intensely competitive sector, the biggest challenge faced by such companies is ensuring that they are in a position to be able set prices in the short-term to maximize their competitive advantage and profitability. The study of pricing will help management to make correct operational decisions.

This study utilizes transaction data, which were obtained from the Taobao e-commerce platform. Taobao is the largest e-commerce retail platform in the world. We analyzed factors, including business models, homogeneity, reputation ratings and sales volumes, which may affect pricing.

This study found that consumers in the baby food sector of Chinese cross-border e-commerce are not price-sensitive. Consumers are reputation-rating-sensitive. The reputation ratings of sellers affect the price dispersion in e-commerce markets. The Core Price Dispersion Rate Model not only considers the prices but also takes sales volumes into account in the calculations. Finally, based on Gaussian processes, a model was developed for price forecasting in the area of cross-border e-commerce. The experimental results show that the proposed method is highly valuable for price forecasting.

This study provides a novel understanding of the baby food sector in the Chinese cross-border e-commerce market by examining the business model, price dispersion, reputation rating and correlation between the reputation of sellers, prices and sales volume. Furthermore, a model for price forecasting is proposed.

The financial crisis starting in 2008 made many European countries opt for a change of exchange rate regime. The choice of price measure as an entry requirement to the European Economic and Monetary Union (EMU) and as input in the monetary policy decision process re‐appeared as an important political and research issue. This paper aims to argue that, considering the importance of producer prices in international competition, their role is underplayed by policy makers and researchers.

Producer prices are analyzed in the transition from national exchange‐rate regimes to the EMU for 13 two‐digit manufacturing sectors in the first 11 countries to adopt the Euro.

It was found that significant price convergence before 1993‐1998, but no or modest evidence of convergence after 1998‐2005 when the Euro was introduced. This pattern is partly different from what prior studies have found for consumer prices, and is consistent with the change of exchange rate regime to a monetary union anchoring inflation rates. A conditional β‐convergence analysis reveals effective exchange‐rate changes and differences in cyclicality as important determinants of price convergence, suggesting that import of inflation is an important determinant of price developments in the EMU.

The paper concludes that considering the role of producer prices and their deviating pattern from consumer prices, producer prices are underplayed in the research and deserve more attention. It is argued that increased attention to producer prices is warranted.

Focusing monetary policymaking on consumer prices alone appears inefficient. Rather, then, support for the trade‐off approach in monetary policy‐making is supported.

In considering different solutions to the financial crisis, increasing attention should be paid to the development of producer prices.

This is the first study to focus on producer prices in the research on the transition from a national exchange rate regime to a membership of a monetary union.

This paper investigates prices of consumer electronics sold on the Web by both online‐only retailers (Dotcoms) and the online branches of multi‐channel retailers (MCRs). Surprisingly, it finds that Dotcoms charge higher price than MCRs, a conclusion contradictory to the results of most of empirical studies. Also finds that the electronics prices decreased over the period of study in general, dropping about 0.6 percent per week, and the prices of MCRs and Dotcoms went down with time at a similar speed. Further, the prices across MCRs are 35.3 percent more dispersed than the prices across the Dotcoms based on full prices, and 33.1 percent more dispersed based on percentage prices. However, results show that price dispersion moved up with time in general, with no significant difference in the speeds between MCRs and Dotcoms.