آشنایی با تلاقی ویژگی های خرده فروش، ویژگی های بازار و استراتژی های قیمت گذاری آنلاین

Theories from Information Systems, Marketing and Economics suggest that product, retailer, and market characteristics jointly serve as determinants of online retailers' ability to price differentiate. Until now, the empirical research has focused on examining the impact of these determinants in isolation. In this paper, we extend the prior online price dispersion literature by examining the interactions among product, retailer and market characteristics. We construct a multi-level hierarchical linear model to empirically test whether market level characteristics moderate retailer characteristics in explaining price dispersion. Our analysis is based on a dataset of 13,393 price quotes for 1880 best selling products across eight product categories from 194 online retailers. The analysis indicates that service quality has a positive effect on retailer price levels. We observe that the relationship between competitive intensity in a market and retailer price levels is inverted “U” shaped. In contrast, the influence of the interaction between a retailer's service quality and market level variables on retailer price levels is “U” shaped. These findings together provide the first known empirical evidence for the existence of mixed pricing strategies among online retailers. Contrary to conventional wisdom, we find that retailers providing quality service are able to charge higher prices as the competition increases.

The growth in Internet based retailing3 has been accompanied with equal interest amongst researchers examining the impact of the Internet-enabled business models. Central to online retailing is the informational transparency provided by third-party websites such as Pricescan.com for comparative product prices and number of competitors, and Bizrate.com, which also provides service quality ratings and consumer opinions of retailers. Such transparency, accompanied by ease of search, was predicted to provide gains in informational efficiency and reduce price dispersion in the marketplace [6] and [7]. It has been suggested that the increased availability of information accompanied with the ease of search will lead to cost transparency [35]. This will allow the consumers to clearly see through not just the prices but also the cost structures of sellers and suppliers. This, in turn, will lead to substantial erosion in sellers' ability to price differentiate and extract premiums, and lead to informationally efficient markets. Yet, empirical evidence from a wide range of product markets and countries indicates that price dispersion is persistent in online markets and that the so-called “law of one price” does not hold [3], [5], [9], [10], [11], [13] and [18]. The persistence of the price dispersion implies retailers' ability to sustain price differentiation even in the face of increased search efficiency and accessibility to a host of other relevant information. The question arises, what are the primary sources of differentiation that influence a retailer's ability to extract economic rents? As can be expected with early work in an area, the vast majority of research has focused on isolated aspects of informational transparency and the resulting impact on price dispersion. Studies shedding light on what enables the retailer to price differentiate from its competition (retailer characteristics) have examined retailers' ability to service differentiate. For instance, in eBay auctions, sellers' premiums have been found to be increasing in seller reputation, a proxy for service quality offered [4]. Another retailer characteristic considered is the combination of transaction channels offered; for example, pure-play Internet versus brick-and-click retailers [28]. Another recent study in marketing considers market characteristics such as number of competitors, average price and product popularity [27]. It is worth noting that none of the prior studies have examined the interactions between retailer, product and market characteristics towards explaining price dispersion. Given the enhanced product and retailer rating information disseminated by online intermediaries, we wish to study the impact of this information richness on retailers' pricing strategies. Electronic markets enable volumes and speeds that human middlemen could not accomplish [20]. There has been limited research on the impact of intermediaries, such as price-comparison agents, on price levels and retailer's strategies. It has been shown analytically 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 [23]. Given these theoretical expectations of the impact of widespread information availability, we empirically examine when and how in relation to competitive intensity does retailer service quality and choice of transaction channels shape an online retailer's ability to price differentiate. The key question we address is whether such information, accessible to both consumers and competitors, is being cross-fertilized and acted upon in a significant way. To summarize, we seek to answer the following questions with regard to a retailer's ability to price differentiate: 1. What retailer characteristics matter? 2. When, in context of different market conditions, do they matter? 3. How do they enable different degrees of price differentiation? The rest of the paper is organized as follows. The next section presents the conceptual model for our analysis. It includes five test hypotheses that examine how market and retailer characteristics interact, and in the process determine the scope of price differentiation available to a given retailer. We then describe our data collection from heterogeneous sources to capture the information that is widely available to consumers and retailers alike. We then present a hierarchical multi-level regression model that includes factors at different levels of measurement (product, retailer and market) to capture the richness of the conceptual framework. Subsequently, we report the results of the data analyses and analyze the implications. We conclude by discussing limitations of our study and directions for future research.

Our study contributes to the understanding of the sources of price differentiation among Internet-enabled retailers. We investigate the impact of widespread information availability made possible through IT on pricing strategies of retailers in electronic markets. In this context, we evaluate whether differentiation in service quality and transaction channels affects retailer prices in electronic markets, and if so, how and when in relation to market characteristics does providing quality service and multiple channels of transactions enable online retailers to price differentiate. Examining influences from multiple sources in a unified hierarchical linear modeling framework, we observe that retailers providing medium to high service quality levels can actually benefit from increased competition. While several prior theoretical studies [6] and [14] have suggested that increasing competitive intensity in a market can benefit established, branded or high service quality retailers, to the best of our knowledge, ours is the first study to empirically support this claim. The results also support the findings of [4] and [19] that trust with a retailer and the reputation of a retailer are major determinants of premiums in electronic markets. In addition, we also find that market level influences have a significant role in determining a retailer's ability to charge premiums. For books, camcorders, DVD players, and printers the two market level characteristics, competitive intensity (as measured by number of competitors) and average price level are able to explain all the variation in prices attributable to the differences across the various products. We find support for our hypotheses that retailers who provide better service quality also charge higher prices. This implies that retailers seem to consider providing better service as a means of differentiation. Our results also show that the influence of service quality on retailer prices varies in a non-linear fashion with the number of competitors in the market. Up to a certain threshold, retailers with low service quality increase their prices as the number of competitors in the market increases. However, beyond the threshold these retailers decrease their prices with increased competition. In contrast, the high and medium service quality retailers decrease their prices with an increase in the number of competitors until a certain threshold, beyond this threshold, these retailers then increase their prices with increased competition. This contradicts the prediction of Porter [31] that increased competition accompanied with enhanced access to competitors' price information would reduce a retailer's ability to price differentiate. We conclude that in electronic markets there is room for mixed pricing strategies. Theoretical expectations based on mixed price strategies suggest that the existence of infomediaries could potentially create at least two consumer segments — the price conscious consumers who use the price scan agents to search for the lowest price for any product and the value conscious consumers who use rating agents such as Bizrate.com as a credible source of retailer reputation and chose the retailers who are good in service quality. Under these circumstances it is optimal for retailers to increase their prices as the number of competitors in the market increases. We also believe that the high and medium service quality retailers are able to charge higher prices when the number of competitors in the market is very high due to the DIF-ness phenomenon [14]. Although consumer search costs are low in online markets, when the number of competitors in the market increases, retailers with good service quality are able to differentiate better because consumers are able to compare the value provided by these retailers relative to the service quality provided by a large number of low service quality retailers. Our analyses also indicate that retailer channel structure significantly influences the prices charged by the retailers. Importantly, we observe that the national brick-and-click retailers charge higher prices. This is probably due to the trust they engender among online shoppers given their national presence and associated brand recognition, and the increased convenience they provide to consumers. Lastly, we find that while average price level is an important determinant of price dispersion, the relationship between average price level and price levels is not robust across product categories. Overall, the results imply that due to the ability of online retailers to differentiate based on service quality and the impact of information overload on consumers, the predictions of the electronic market hypothesis (EMH) are not validated in electronic markets for homogenous products. EMH predicts that by reducing coordination costs, information technology (IT) will shift industrial organization from hierarchical to market-based forms of economic activity. In contrast, we find that the market power for the firm is being reinforced by the widespread availability of information regarding prices and service quality in electronic markets. Such information provides retailers an effective and credible source of price differentiation. The emergence of websites such as Bizrate.com provides credible sources of quality information to consumers (especially as competition increases) and also helps retailers that provide quality service to extract higher premiums. Current price dispersion research is limited by not having access to supply-side cost data. In addition, future research is needed in accounting for revenue measures that take into account where in the price band do actual e-commerce transactions take place. It could be possible that the dispersion among products where transactions are made is different from the dispersion in retailer prices. Another limitation of our work is that we do not consider market factors such as product life cycle. Such a study would imply the necessity of longitudinal data. Also, pricing is one of the many strategic decision criteria that a retailer has to manage in order to optimize profits. For example, a retailer is also interested in building a market share, and in ensuring consumer retention. Future studies should compare the influence of service quality across these different decision criteria and investigate the process through which they lead to optimal profits for retailers. Our results indicate channel choice affects the pricing strategy of the online retailer. In fact we find that retailers providing multiple channels of transaction also charge higher prices. Future research should investigate whether providing multiple channels of transaction also increases the revenues of the retailers, and why providing multiple channels of transaction affects consumer choice. Given that price dispersion as a metric signals the confluence of consumer search, retailer pricing strategies and informational efficiency of markets, we hope that our integrated approach will be useful to other researchers examining the interactions between these competing forces in electronic markets.