In this article, we calculate various distance metrics to measure product differentiation by observing consumer search behavior directly. We compare these measures by analyzing a dataset of 1,642 digital cameras with 85 product characteristics and show that differences in the product characteristics are correlated with some of the measures of distance to a surprisingly high degree. Furthermore, we demonstrate that products categorized as having more substitutes according to our metrics appear to face stronger competition, resulting in lower prices. We also find significant price effects from distant competitors, challenging traditional assumptions about limited competition. The Jaccard index and a newly proposed weighted frequency-based metric outperform the alternative measures of product differentiation and effectively capture substitutability in multi-attribute spaces when it is impossible to calculate cross-price elasticities.

In this article, we provide a novel measure of product differentiation by observing consumer search behavior directly. We track individual consumers in a price search engine and generate a measure of distance in product space, based on goods surveyed conjointly within individual search episodes. Comparing with indices proposed in other studies, we show that our measure outperforms many of the other metrics in an application to 1642 digital cameras that differ in terms of 85 product characteristics. These differences in the product characteristics are correlated with our measure of distance to a surprisingly high degree, and prices are influenced by a large number of other adjacent products along the multi-dimensional space of product characteristics.

In this article, we provide a novel measure of product differentiation by observing consumer search behavior directly. We track individual consumers in a price search engine and generate a measure of distance in product space, based on goods surveyed conjointly within individual search episodes. This metric performs well in an application to digital cameras as an example of complex products. Regression results show that differences in product characteristics are correlated with our measure of distance to a surprisingly high degree, and that prices are significantly lower if products have to compete with a larger number of close substitutes.

We analyze price dispersion using panel data from a large price comparison site. We use past pricing behavior to instrument for potential endogeneity that might result from the selection of firms to certain product markets. We find that greater price adjustment costs result in greater price dispersion. Although the impact of price adjustment costs on price dispersion became weaker over time, the causal effect of price adjustment costs on price dispersion is still present at the end of the period. Our results are robust to many alternative empirical specifications. We also test a range of alternative explanations of price dispersion, such as search cost, service differentiation, obfuscation, vertical restraints, and market structure.

The choice of an appropriate e-commerce strategy for the listing in price comparison platforms (eBay, Amazon, price search engines) is crucial for the survival of online stores in B2C e-commerce business. We use a comprehensive data set from the Austrian price search engine geizhals.at to identify successful e-commerce strategies with regard to these listing decisions. An e-commerce strategy is a set of choices including listing, availability, and decisions on the price path and shipping cost. We apply cluster analysis to identify the different strategies that have been used by online retailers. Using various success measures such as revenue, clicks, market share, and the survival of firms we present causal evidence on the effectiveness of different e-commerce strategies.

E-commerce has become an integral part of the world's economy. In this study we investigate the impact of service quality in e-tailing on site visits and consumer demand. Such an analysis is important given the almost Bertrand-like competitive structure. Our analysis is based on a large representative data set obtained from a price comparison site covering essentially the complete Austrian e-tailing market. Customer evaluations for a broad range of 15 different service characteristics are condensed using factor analysis. Negative binomial regression analysis is used to measure the impact of service quality dimensions on referral requests to online shops for different product categories. Our results show that the most important service quality aspects are those related to the ordering process and the firm's website performance.

The choice of an appropriate e-commerce strategy is crucial for the survival of online stores in B2C e-commerce business. We use a comprehensive data set from the Austrian price search engine geizhals.at to identify successful e-commerce strategies. An e-commerce strategy is a set of choices including the listing decision, availability decision, and decisions on price and shipping cost. We apply cluster analysis to identify the different strategies that have been used by online retailers. Using various success measures such as revenue, clicks, market share, and the survival of firms, as dependent variables in our regression analyses, we present empirical evidence on the effectiveness of different e-commerce strategies.

We analyzed the impact of social networks on general practitioners' (GPs) referral behavior based on administrative panel data from 2,684,273 referrals to specialists made between 1998 and 2007. For the definition of social networks, we used information on the doctors' place and time of study and their hospital work history. We found that GPs referred more patients to specialists within their personal networks and that patients referred within a social network had fewer follow-up consultations and less inpatient days thereafter. The effects on patient outcomes (e.g. waiting periods, days in hospital) of referrals within personal networks and affinity-based networks differed. Specifically, whereas empirical evidence showed a concentration on high-quality specialists for referrals within the personal network, suggesting that referrals within personal networks overcome information asymmetry with respect to specialists' abilities, the empirical evidence for affinity-based networks was different and less clear. Same-gender networks tended to refer patients to low-quality specialists.

Using a matched insurant-general practitioner panel data set, we estimated the effect of a general health-screening program on individuals' health status and health care cost. To account for selection into treatment, we used regional variations in the intensity of exposure to supply-determined screening recommendations as an instrumental variable. We found that screening participation substantially increased inpatient and outpatient health care costs for up to two years after treatment. In the medium term, we found cost savings in the outpatient sector, whereas in the long run, no statistically significant effects of screening on either health care cost component could be discerned. In summary, screening participation increases health care costs. Since we did not find any statistically significant effect of screening participation on insurants' health status at any point in time, we do not recommend a general health-screening program. However, given that we found some evidence for cost-saving potentials for the sub-sample of younger insurants, we suggest more targeted screening programs.

The aim of this project is to investigate the competitive behaviour of e-commerce firms over the course of the product lifecycle for consumer electronics such as digital cameras, IT hardware, and smartphones. We combine data from Austria's largest online price comparison site with retail data provided by an industry-specific price comparison site for consumer electronics. This aggregated database enables us to record firms' input prices as well as to monitor the various moves each firm makes with regard to strategic market entry and pricing for hundreds of product markets. Insight into e-tailers' market behaviour is key to understanding online markets, which are reaping an ever greater share of retail sales each year. Yet antitrust and regulatory authorities are also interested in knowing how many firms are needed to sustain competition within a market, for merger assessments focus in part on the expected relation between the number of firms in a given market and corresponding market outcomes, i.e. product price and quality. Clearly, questions related to competition and pricing are of central importance to society and the public, as a minimum level of competition is needed to ensure sufficient supply of a product at reasonable prices.

Volunteering participation rates vary greatly across countries even when the potential volunteers’ individual characteristics are controlled. We therefore analyze the volunteers’ motives against the backdrop of the predominant political and economic environment in different countries, focusing on the state’s role in influencing an individual’s decision to volunteer. Combining individual-level data from the European and World Values Survey with macroeconomic and political variables for OECD countries, we identify three channels through which governmental activities influence voluntary labor: size of the state (i.e., amount of public social expenditure), political consensus between voters and the government, and government support for democratization.

We analyze the interaction between market structure and market performance and how it varies over the product cycle. To account for the potential endogeneity in this relation, we use an instrumental variable approach. We combine data from the largest Austrian online market for price comparisons with retail data on wholesale prices provided by a major hardware producer for consumer electronics. Our results show that instrumenting is important for estimating the empirical effect of competition on the markup of the price leader. One more firm in the market is associated with a reduction of the price leader׳s markup which is equivalent to competition between existing firms for an additional 3weeks in the product life cycle. Our results support search theoretic models and contradict models of monopolistic competition. Moreover our results support the existence of price dynamics over the product cycle. They also highlight the substitutability between newly innovated and old expiring technologies and how it varies with respect to competitors׳ and own brand innovations.

We investigate the impact of self-organized reputation versus certification by an independent institution on demand for online shops. Using data from a large Austrian price comparison site, we show that quality seals issued by a credible and independent institution increase demand more than feedback-based reputation. This result is important for markets where the market-maker must deal with issues of asymmetric information concerning the quality of goods and services in the market.

We conduct an empirical study on the search and purchasing behavior of buyers on an Austrian price comparison site. On such a market a consumer typically searches for the cheapest price of a given product. Reliability and service of the supplier, however, are other important characteristics of an offer. We find robust evidence of consumer behavior that can be described as a two-stage procedure: shoppers first select a group of candidate offers based on the price only; then, in the actual buying decision consumers tradeoff a lower price with higher reliability of the retailer.

Basu (2006) argues that the prevalence of 99 cent prices in shops can be explained with rational consumers who disregard the rightmost digits of the price. This bounded rational behaviour leads to a Bertrand equilibrium with positive markups. We use data from an Austrian price comparison site and find results highly compatible with Basu’s theory. We can show that price points - in particular prices ending in 9 - are prevalent and have significant impact on consumer demand. Moreover, these price points are sticky; neither the price-setter itself wants to change them neither the rivals do underbid these prices, if they represent the cheapest price on the market.

Setting prices ending in nines is a common feature of many markets for consumer products. This prevalence has been explained either by a specific image of such price points or by the exploitation of rational inattention on the part of the consumers who want to economize on the cost of information processing. We use data from an Austrian price comparison site and find a remarkable prevalence of such price setting. Prices ending with nine are also sticky: price-setters change them with a significantly lower probability; rivals underbid these prices more seldom if they represent the cheapest price on the market, and we observe higher price jumps by price leaders for these price points. Finally, we explore the impact of these price points on the consumers' demand.

Basu (2006) argues that the prevalence of 99 cent prices in shops can be explained with rational consumers who disregard the rightmost digits of the price. This bounded rational behaviour leads to a Bertrand equi- librium with positive markups. We use data from an Austrian price com- parison site and find results highly compatible with Basu's theory. We can show that price points - in particular prices ending in 9 - are preva- lent and have significant impact on consumer demand. Moreover, these price points are sticky; neither the price-setter itself wants to change them neither the rivals do underbid these prices, if they represent the cheapest price on the market.

This paper investigates the impact of service quality in e-tailing on site visits and consumer demand (approximated by the last-click- through concept). We use a large representative data set obtained from a price-comparison site which covers most of the national (Austrian) market on e-tailing. Customers' valuations for a broad range of 15 dif- ferent service characteristics are condensed by factor analysis. Negative binomial regressions analysis is used to measure the impact of princi- pal factors for service quality on referral requests to online shops and last-click-throughs for different product categories.