A Novel Case of Group Buying Infomediary. Groupon.com, the fastest growing web-company

Contents

PART ONE
Introduction

Chap I. Internet Economics
1.1 Towards new consuming channels: E-shopping or traditional retailing?
1.2 Trust in E-Commerce Customer Relationships
1.3 Reputation within the online market frame: The case of a C2C online auction market.

Chap II. Information and reputation in intermediated product markets
2.1 Intermediation and information
2.2 Infomediaries and competition in search markets
2.3 Intermediation and reputation in online markets

Chap III. Markets with intermediated goods
3.1 Intermediaries as dealers
3.2 Intermediaries as matchmakers
3.3 Intermediaries as two-sided platforms
3.4 Double Marginalization in vertical relation
3.5 Coupon Economics: A product of economic recession?

Chap. IV E-Tailing: The online shopping pandemic
4.1 Traditional retailing and/or e-tailing: Complements or substitutes?
4.2 A case of e-retail complementarity to traditional commerce: Groupon.com
4.3 Finding the “fake” Bertrand equilibrium price
4.4 Efficiency and Customer satisfaction

Conclusions

PART ONE

Introduction

It has been more than two decades since internet boosted its potential and now it can be considered a fearful competitor of many mortal businesses such as retailers, advertisers or even intermediaries. It is also known that the advent of internet in our daily life has also changed many systems’ structures such as the transaction costs in B2B, B2C or even the C2C models. Internet has abolished geographical boundaries, connected people and facilitated information flow. We now live in a world that everything happens in real time, which also brought changes in economic equilibriums, marketing strategies as well as speculation margins. Amazon, Google, EBay has revolutionized the custom of traditional shopping, increasing consumer’s addiction to consumption by differentiating products in every possible and imaginable manner. Well, this work’s attempt is to shed a light on the dynamics of this evolution, to acknowledge the main players and see how equilibrium can be set and re-set incessantly in a very volatile market due to its lack of physicality (i.e there is a physical gap between supplier and demander at the purchasing moment, therefore is very difficult to build customer loyalty). The example used to extrapolate some statistical evidence is linked to group buying e-commers such as coupon companies. It is the case of Groupon.com, the daily offers company with the highest growth rate among web companies since 2008^[1].

The first part of the study is a theoretical literature review mainly arranged to give a theoretical backup to the empirical analysis that will follow. It seems that there has been a lot of field research on the topic. I suppose the reason is the worryingly fast growing pattern of these virtual business realities. The first chapters aims to concatenate the main features of these new business models, trying to understand the differences between them and the traditional ones which offer the same products or services- also the reasons why “normal” firms are greatly suffering market share losses. The third chapter instead is totally dedicated to online intermediaries since they seem to be the economic agents to have better fit in this new giant virtual marketplace. Different types of intermediaries obviously play different roles in the business arena and also provoke different welfare effects in terms of costumer’s wellbeing. For such reasons the interesting part here is their game strategy while intermediating either information or services.

Finally the last chapter presents an empirical analysis based on the sales data of Groupon’s Italian branch. Here we try to see the intermediary’s behavior in confront to the other firms/partners, how their mark-up is being set and what are the market drivers to such strategies.

Chap I. Internet Economics

It’s by now a worldwide awareness that we are witnessing an addictive interest in the use of the Internet. The advocates of the so-called “New Economy” claim that we entered a new era with high output growth, lower unemployment and lower inflation. Investments in information and communication technologies (ICTs) have showed a positive impact on productivity and the increased use of Internet played an important role in this claim. The literature suggests three different explanations for the lower inflation experience: increased productivity growth combined with slow adjustments of wages, improved credibility of monetary policy and improved the functioning of the labor market. Meijers H. (2006) provides another explanation where adoption of Internet as a cost reducing and efficiency improving technology, changes market structures and affects the mark-up margins of firms and thereby the relation between costs and output prices. In his paper the diffusion of Internet as a cost saving technology is introduced in a model with network effects and dynamic market structures: an endogenous diffusion process for B2B commerce.

The dynamics of this system imply that in the initial phase of the diffusion process, the mark-up on marginal production cost will increase. This is caused by the monopolistic behavior of few Internet users. As more firms invest in Internet, competitive pressure starts to increase both among the users of the Internet and among the non-users and the mark-up starts to decrease. This evolution of the mark-up is the same as the one found by Brayton et al. (1999) in their search for an explanation of low inflation in the information-based economy: diffusion causes low inflation if we assume constant wages and other price’s factors. By the other hand, if the diffusion process stops, even in the case where some firms do not invest in the Internet, the markets return to a situation with a constant mark-up on unit production cost and constant prices. However, the model also predicts that the inflation suppressing effect of the increased use of Internet eventually will cease and that inflation will increase in the longer run.

The missing perspective of Meijers’ model is the supply side of intermediary goods and the use of the Internet by these firms (see chap III). This perspective can give a more complete view on the entire value chain of products and services. Including the final product market would make the whole picture complete. Thus, sprung corollary so far, might be the analysis of the intermediaries’ role in the exploitation of an internet-based business, especially their cost/profit function, i.e. their welfare properties.

As a backup literature is the work of Michael Y. Yuan (2006)^[2], which gives an example of how the online intermediaries (OIs) such as eBay, Orbitz, Amazon.com, Netflix, iTunes, and AuthorHouse , are becoming more and more important market institutions. Their conduct affects the welfare of great numbers of both sellers and users on OIs. The paper suggests that some OIs may be natural monopolists: Ebay, Netflix, and iTunes, for example, have 95%, 95%, and 70% shares of their respective online markets of auction, book selling, and music^[3]. According to this study, there are two reasons why OIs might intrinsically be inclined to structure themselves as monopolists: the increasing returns to scale in the industry (OIs may incur high fixed costs to set up their facilities, but realize very low marginal costs in providing their services); as well as, their positive indirect network effects across sellers and buyers (see chap.III, section 3.1). In synthesis, the model considers competition from potential entrants and monopolistic competition amongst product creators; describing pricing, sizing and their entry decisions. Here competition from potential entrants can cause the digital library (i.e. Amason, Ebay, iTunes) to behave in a manner that leads creators to over-invest in creation, and to over-supply information products. Also, the over-investment is more severe when cost of entry is lower; and less severe when information products are more differentiated^[4].

Concluding, all the examples so far embedded seem to lead to the next questions: How do IOs exploit their function? Why do Users (i.e platform affiliated-customers) have the perception that Infodealers (i.e Intermediaries that mediate by offering information and services contemporaneously) may concur negative profits? Why do Users have the perception that they purchase at lower costs by consuming Infodealers’ products and services?

Obviously, there’s no simple answer to these questions. This works ‘attempt is to open an alternative window in interpreting the behavior of the above economic agents. Thus, it seems interesting to first understand the genesis of IOs evolution: the following section gives an introductory comparison between traditional and online intermediation.

1.1 Towards new consuming channels: E-shopping or traditional retailing?

We now may agree that Internet has revolutionized customer behavior since its very first days of commercialization. The issue of measuring this impact instead, evokes many discussions among traditional or digital literature on the subject. Continuing in this picture frame, it seems that the substitution or complementary role of Internet products and/or services is a question frequently posed by researchers interested in the impact of the Internet on society. It has the potential to alter daily activities such as work (through telecommuting), shopping (through e-shopping), networking ( linkedin, Tweeter, Facebook) etc . Especially for retailing, online merchandising can have serious consequences, as it has the potential to make existing retail business models redundant (Wrigley et al., 2002; Burt and Sparks, 2003).

The advent of e-retailing provides an opportunity to experiment comparisons with classic economic models. Current research on the relationships between online solutions, search costs and competition, in many ways, mines existing theories on the economic effects of advertising. Traditional marketing postulates that the degree of information gathered from advertising depends in large part on the particular attributes of the product. For example Nelson (1970) differentiates between search and experience goods and the importance of these attributes on the effects of advertising. Similar categorizations are helpful in examining the impact of digital marketing on the collection of information by consumers and the subsequent behavior of firms.

Never the less the first main impact existence of online retailing produces is the need to reclassification of products based on their particular characteristics that can be marketed in this new virtual business world. Such reclassification can be spotted in the Colleen A. Fahy (2005)’s work where it is distinguished between “visual” and “tactile” goods. The qualities of the firsts can be determined simply by looking at an image of the product and/or by reading its description. While such products certainly exist, there are many others whose qualities can only be judged in person such as the fit of a pair of jeans, the comfort of a chair etc. These sorts of qualities can be confirmed before purchase but the consumer must come into contact with the actual product, thus they are qualified as “tactile”. There is still a third hybrid type: some products will have both visual and tactile characteristics. But as always happens when trying to categorize qualitative properties, individual emphasis on certain qualities may vary as well. One person may buy a piece of furniture simply based on how it looks, another will want to examine how it is put together and how the fabric feels. In an effort to simplify the theoretical model, this theory assumes that a good is visual or tactile, not both because author’s goal is to present an oligopolistic price setting model which examines the role of product characteristics on the profitability of firms in traditional versus e-commerce settings. Characteristics may include the visual or tactile nature of a product as well as the degree of differentiation between the products of competing firms. Experience goods are not incorporated into the analysis. The model focuses on the difference between information gathered digitally and that garnered from an in-person inspection. This distinction is not applicable to experience goods^[5].

Most of the literature on e-commerce has focused on the idea that in the world of the internet, search will become frictionless and firms selling homogenous products will face zero profits. Recent empirical research proves and the results are mixed^[6]. Both geographical distance and product space differences should be factors placed under consideration when compared with the traditional address model which would perfectly fit for the comparison. An example is the the geographical location model of Hotelling’s (1929). After Hotelling’s work the application of “distance” to product characteristics was introduced^[7]. Both models are known address models.

Other examples are Bakos (1997) and Lal and Sarvary (1999) works. Bakos extends Salop’s (1979) circular city, “M” firm model to include a constant cost term for finding a product’s price and/or product attributes. He finds, among others, that increases in search costs will lead to increases in pricing and profits. In addition, high search costs may lead to market breakdown where acceptable products exist for consumers but they do not search due to high costs. Thus, his argument is that the internet, in reducing search costs, may reduce market breakdowns. Lal and Sarvary by the other hand, assume that products have a degree of non-digital, or tactile, attributes. They assume two products, one of which the consumer is already familiar. They also assume “destination shopping” such that the marginal cost of going to the first store is larger than that of visiting the second. The approach to be used here differs in that of the location models since it assumes that consumers are located in-between the firms thus the costs of going to the second store may be higher than going to the first. It will also be assumed here that consumers are no more familiar with one firm’s product than the other.

Turing back to Colleen A. Fahy ‘s (2005) model, while usually models may be used to make a number of observations and comparisons, this one focuses on the examination of the relative success of internet firms for each type of good (visual or tactile) as well as relative profitability of stores versus internet firms for a given type of product. Specifically, the model provides insights into the following three questions:

- Which type of outlet is foreseen to be more successful when selling differentiated visual goods; traditional stores or internet retailers?
- Which type of outlet is predicted to be more successful when selling differentiated tactile goods, traditional stores or internet retailers?
- Finally, which type of product will an online business be better off selling, visual or tactile?

The analysis of tactile goods differs from that for visual goods because, in the absence of perfect information, consumers may search for the best possible product. In addition, considerations in undertaking such a search and the specific manner of search will differ depending on whether the product is sold in traditional stores or through an internet site. Model’s results show that for visual goods as well as tactile goods where search does not occur, as long as consumers are particular enough about product attributes, traditional stores will have no advantage over internet companies. In the case of tactile goods when search does take place, the considerations and manner of search create differences in profitability for the two types of retailers. Finally, since for internet companies there is no difference in profitability for tactile and visual goods, consumers will search for the best product. If there is no search, profitability will depend on actual versus expected product attributes.

For decades, address models have demonstrated that the key to reducing competition and increasing profitability is to provide products, which are differentiated by location, attributes or both. Because the world of e-commerce eliminates geographical differentiation, the literature suggests that internet companies may face fierce competition and may be less successful than traditional stores if their products are not sufficiently and importantly unique. As presented above it is predicted that this will be true not only for visual goods but for tactile goods when consumers do not find it in their best interest to search. However, again if conditions are such that consumers will not search, if products are adequately differentiated and consumers care about the differences, travel costs will cease to constrain decisions and traditional stores will no longer have an advantage over internet firms. As in every model the results are true if any of the following are true: full information is available (visual goods), products meet or exceed expectations or if searching is prohibitively costly.

Though, the collateral issue can be that some information cannot be communicated effectively through digital means, if a consumer is sufficiently disappointed in his first selection and searching is not prohibitively expensive, he will go out and look for a product that better meets his needs. When firms face consumer search, many of the customers initially lured by lower prices will leave, thus reducing the incentive to lower prices. Therefore, somewhat ironically, the presence of search increases profitability. This is true for traditional retailers and online firms alike. However, while search benefits both types of firms, its effect will differ. Because e-shoppers are not constrained by geography, these types of firms seem to be more easily affected by search. However the positive effects of search turn out to be somehow mitigated for online firms because consumers, upon examining both products, can decide to keep their original choice without penalty.

Finally, when deciding which type of good is better suited for digital sale, the question of search once again arises. In this context, if consumers search, then tactile goods become visual goods and each type of product would be equally profitable under this categorization. However, if consumers do not search, firms may be able to take advantage of the consumer’s lack of information. Since profitability will be based on perceived differentiation, if potential buyers can be convinced that the differences between products are greater and more important than they actually are, firms will benefit.

The model demonstrates that when consumers require getting in contact with a product in order to access its features, the relative advantage of searching for products online can both help and hurt e-commerce retailers. Additionally, it was shown that for tactile goods, when search does not occur, profits are dependent on consumer’s perceptions of product differences. How would be then if firms are able to manipulate information and change consumer expectations or perceptions? – According to the above studies we can assume that e-firms can distort either consumers’ expectations or perception and as a result even his consumption behavior. For such reasons the issue that might arise is modeling and forecasting these distortions. Anyhow, it does indeed seem to be avery interesting filed for further research.

A peculiar vehicle to lever with in order to influence customer expectations for E-firms is Customer Trust. This concept anchored in a e- firm business strategy seems to influence it’s purchasing (see Gefen, D (2000), McKnight and Chervany (2002), A.F Salam et al. (2003) ). The next section will give some explanatory examples.

1.2 Trust in E-Commerce Customer Relationships

Online marketplaces nowadays are reaching (if not yet done) their maximum boost. Customers are less and less reluctant to engage in spontaneous transactions online. However it was not like this just few years ago. According to a 2001 McKinsey & Co. research report, lack of consumer trust is a critical impediment to the success of e-commerce^[8], a conclusion we are considering less valid today^[9] but still greatly considerable. In less innovative markets consumers may still fear providing credit card information to online commercial sellers, simply because they lack enough trust to engage in business relationships involving financial transactions (D. Hoffman et al 1999). It follows that many customers may still not trust the selling party when it comes shopping online. Thus, it is precisely the development of electronic money exchange flows that are crucial to understand the role of trust and its mechanisms in the context of e-commerce. Literature on psychology teaches that trust does not exist in a blank box; it will require the context of a “relationship and space” to develop. Alternately, it is difficult to imagine any exchange that could be developed and bred without trust. While a secure and sophisticated infrastructure is necessary, A.F Salam et al. (2003) by the other edge states that it is not sufficient for building the trust required to generate spontaneous electronic transactions on the web. They say that reliable encryption and authentication methods are common technical approaches to ease this problem. Digital certificate technologies (such as eTrust, WebTrust, eCard, and Smartcard) have now become broadly utilized and a trending market. Secure transaction methods using encryption and other technologies have existed for some time, yet Liu, C, Marchewka, J. et al (2005) show that the perceived risk of online transactions is still significant. As with any innovation (in particular virtual ones), the market needs time to adjust the perception of a new trust schemas in order to decide on adoption and diffusion that would lead to widespread acceptance.

In 2003, Salam, A.F, Rao, H. R, & Pegels, C. C, highlighted an interesting aspect: the major expectation of web entities is their potential for online shopping and benefits deriving from cost reduction, for both consumers and businesses. Their article analyses the perceived risk on performing financial transactions where their money is exposed; or any other financial asset, being real or virtual, which in simple terms would prevent the spontaneous transfer of financial assets between consumers and online firms. In other words, trust would remove the obstacle to transform web seller become a complete marketing, sales, and transaction medium. Social networking research indicates that concepts of institutional trust and economic incentives help to build up a framework that serves as a shield to smooth or until even actually reducing the perceived risk. It seems interesting to understand how these concepts integrate together at the same time anchor in a “Max –Profit” business strategy. For the purpose, the authors gave the following definitions:

Social Exchange Framework: “ Exchange processes require the transfer of assets between parties involved in a transaction. This usually involves the transfer of financial assets, equivalent to the agreed upon price of the goods or services, from the consumers to vendors, prior to the actual transfer of goods or rendering of services by service providers. When there is no transfer of financial assets from consumers, very few transactions can be initiated or successfully completed. It allows users to integrate risk into the decision of the other party as to whether or not to engage in the transaction. The incorporation of risk into the decision can be treated as the symmetric alter ego of “trust” (Coleman, J., 1990).” As above stressed, trust is a key element which absence would undermine the presence itself of online markets.

Trust and exchange process, institutional structure, and economic incentives:

“Time asymmetries in delivery introduce risk (perceived or real) into transactions for the parties who must invest resources before receiving a return (Coleman, J., 1990). Sometimes the risk may be reduced by use of contracts that can be enforced by law, but for many reasons, contracts cannot always serve this purpose. For instance, it may not be practical for many online transactions where the value of the product is not high enough to justify the cost of drawing up contracts. Trust plays a key role in many such transactions that occur over the Internet” (Knights, D., Noble, F., et al., 2001)

Trust and exchange process: Granting of trust involves putting resources in the hands of parties who would use them to their own benefit, to the trustee’s benefit, or both (Jones, S., Wilinkens, M., et al., 2000). Coleman, J., (1990) argues that if the trustee (i.e the asset manager) is trustworthy, the person who places trust is better off than if trust were not placed, whereas if the trustee is not trustworthy, the trustor (or the risk bearer) is worse off than if trust were not placed. Differently, it looks like it is in the interest of the risk bearer to settle exchanges with a trustworthy. Here it comes the pain: virtual exchanges create the grounds for risks perception distortions that is why it is necessary to develop social structures or institutions where trustees’ interests stand on through trust rather than distrust. Some of this interest is embedded in the market mechanism while others are mixed in the social fabric. The literature suggests that this is the type of mechanism used by reputation-based systems such as at e-Bay, Amazon.com, and other similar Web communities facilitating transactions over the Web (i.e market places). Therefore, social and economic institutions role have become might increasingly important while fostering and seeding trust in exchange processes.

Institutional structures as intermediaries in trust: the authors distinguish three different kinds of intermediaries by trust exploitation. They are called intermediaries serving as advisors, guarantors, or entrepreneurs. In the e-commerce environment and especially from the consumers’ perspective, the intermediary in the guarantor role is the most important one. Financial institutions, such as banks and credit card companies, have largely played the role of guarantors in economic exchange. These institutions create and cultivate an “institutional trust” among consumers and businesses. This institutional trust is one of the fundamental requirements for e-commerce to flourish, by actually reducing the perception of risk on money transaction as above detailed. According to Salam (et al. ), even when the guarantor experiences a loss of resources if the final trustee violates trust (such as a seller who refuses to give refunds for defective products), the guarantor takes initiatives so that their own trustworthiness in front of the trustor is not perished.

Economic incentive and added consumer value: Despite the risks involved with online transactions, the authors observe that web users do engage in economic transactions and do provide financial information (ie credit card or bank information). The theory claims that these users perceive the risk associated with e-commerce transactions and such perceived level of risk may decrease with the existence of economic incentives that add value to their business such as lower priced goods, reduced search cost, better quality product, and so on. It goes further by arguing that the situation changes from perceived loss to gain as the price differential between products advertised in traditional outlets increases in favor of products available on online sellers/intermediaries (see part 1.1). As consumers find low priced goods of comparable quality, the difference in the price of the product from a traditional shopping outlet is perceived as gain (Jesse W.J. Weltevreden (2006)). As this perceived gain increases along with factors such as convenience and low online search cost, such anticipated gain may be significant enough to reduce the perceived risk of online transaction^[10].

Hence, 3 years before Jesse W.J. Weltevreden further research on the topic, Salam (et al.) proposed that incentives that increase the potential for gain and add value to the consumers tend to reduce the perception on the level of risk so that consumers are more prone to engaging in transactions. In Weltevreden’s perspective, it means that by reducing perceived risk (not necessary real) with other variables constant, customers will prefer e-shopping to the traditional outlet one^[11]

Consumer-perceived risk of transaction over the web. Here, the paper specifically focuses on the perceived financial risk of transactions over online marketplaces. This risk deals with using a payment alternative that will lead to financial losses. For financial loss the author means that the consumer cannot get a refund when needed or is not able to reverse the transaction or to stop payment after discovering the mistake. It also includes fraudulent and sometimes unauthorized use of credit cards leading to financial losses. These are some of the most frequent types of risks that may be associated with marketing and sales transactions. If for some reason the perceived risk in a transaction is too high, consumers are likely to delay the transaction until some form of institutional mechanism is in place to reduce the associated risks. Alternately, they would use different avenues that provide the desired level of protection (using telephone or fax to complete e-commerce transactions).

Concluding, what comes to light from Salam’s work is that the consumer’s perception of risk associated with the transaction will tend to predominate in his/her decision to engage in a transaction. Better depicted in Figure 1, the study of the institutional trust’s and economic incentive role in altering the customers’ perception of risk of e-commerce transaction, is composed by two hypotheses as part of the framework: one, that consumer-perceived risk is reduced with the increase in institutional trust (H1) and, that consumer-perceived risk is reduced with the increase in economic incentives (H2).

Web survey data supported Salam’s (et al.) hypotheses (as presented in the Figure 1). They found support for the hypothesis that consumer-perceived risk is reduced with the increase in institutional trust. Again, this implies that one way to reduce consumer-perceived risk is to develop and increase institutional trust with the involvement of financial and social institutions in the capacity of guarantors in the exchange process. Furthermore, they found that socially recognized and rooted institutions such as banks and credit card companies are perceived to be better candidates for hosting institutional trust compared to little known or non-institutionalized organizations such as unknown web-mall operators or even known mall operators : an emblematic example is Yahoo with its Yahoo! Shopping online mall.

Abbildung in dieser Leseprobe nicht enthalten Figure 1.1 Institutional trust, economic incentive, and consumer-perceived risk of transactions in the context of e-commerce over the Internet (A.F Salam et al. (2003))

1.3 Reputation within the online market frame: The case of a C2C online auction market.

In the previous paragraph we strongly emphasized the importance of trust in building the uprising alternative virtual market (intermediated or not) in parallel to the traditional one. Therefore coming this far, we may agree that the direct link from buyer to seller is indeed forged by the one between Customer Trust and Seller’s Reputation. This link is framed according to consumer perceptions of characteristics such as honesty, credibility, reliability, dependability and discretion demonstrated by the seller. Meaning the consumer would need to build a valuation matrix of the perceived seller’s competence in offering the product design, manufacturing, order processing, delivery, after-sale service, and customer care service as displayed in its online showcase. A seller’s reputation depends in general terms on its “sustainability” to offer good quality products and services along with the ability to respond to emergent consumer needs in timely fashion. As said, traditional retailers can leverage on location, while online retailers cannot (Rayport and Sviokla, 1994). On the other side, when comparing costs, the main balance sheet line for online outlets is the one attract customers (Watson et al., 1998) –i.e acquisition costs. The ability of retail websites to attract online traffic directly affects the volume of business transacted online. Consequently, such customer acquisition or marketing costs remains a major expense for online retailers (Noe and Parker, 2005). Moreover, it may be years before these newly acquired customers deliver a positive return (Blattberg and Deighton, 1996). Closing parenthesis, the most intelligent and effective way to reduce acquisition costs of gaining new customers, as has been demonstrated, is investing in reputation establishment: it is the case of online auctions such as the Ebay’s ones. The aftermath of such schema is managing an intermediation with millions of auctioneers and buyers.

Going back to Ebay, the consumer-to-consumer (C2C) online auction market, has managed to gain a tremendous market shares even though may competitors followed ( i.e Ali-express). Since its start has experienced unprecedented growth and has become the most active segment of e-markets today. EBay, the fastest-growing C2C online auction marketplace, is highlighted as one of the most profitable e-commerce companies because of its continuous innovation. In 2002, a total of US$14.87 billion was transacted on eBay.com, with more than 12 million items listed across 18,000 categories each day (see EBay, Company Overview, (2003)). Studies show that online fraud incidents failed to hinder the fast growth of C2C online auction markets because the reputation scoring schema revealed to be more and more effective for online marketplaces (S. Ba and P.A. Pavlou 2002,. P. Resnick, R. Zeckhauser, et al., 2000). Ebay’s model introduced a very interesting practice, that of tracking post-purchase feedback on each seller, having the best scoring ones more in evidence then the worse ones. The information on reputational scores helps exactly to build the so discussed trust and even prevent potential untrustworthy behaviors as a punitive mechanism. For example, Zh. Lin,D. Li et al., (2004) studied that It would reduce the odds of fraud because, typically, traders are expected to maintain good reputation records in order to maximize their profits. So, their insight is that a reputation scoring system may not only serve as a guide to otherwise fickle entrants, but also help enhance the predictability of existing traders’ behavior and honesty.

Nevertheless, the these systems have attracted researchers from the behavioral sciences and economics keen to investigate the new aspects of reputation in the e-market, such as the impact of online reputation on trader’s trust (e.g., Ref. S. Ba and P.A. Pavlou (2002) and auction price (e.g., Ref. Standifird, S.S., 2001). For the first time it was possible to quantitatively and qualitatively assess reputation of a traded though only valuation scores. In fact, in classical economics studies, reputation is identified as an intangible asset that can indicate a firm’s potential for doing business (Tadelis, S., 1999). Yet, reputation becomes partially assessable in the context of C2C online markets because weighted reputation scores are tracked by reputation systems. This clear and free visibility is why the quantitative research of reputation for the electronic market becomes realistic and feasible. However, these valuable data have not been used in examining the role of reputation in the electronic markets at the macro-level (Zh. Lin,D. Li et al., (2004)). Research into the structure and dynamics of electronic markets might give important understanding on the subject.

In the last decade, the entrepreneurial world has witnessed the fast growth of a world economy empowered by electronic commerce (Barua, A., Whinston, A.B., Yin, F., 2000). Worldwide press interested in online businesses endorsed, testified ad followed the proliferation of thousands of e-commerce from agriculture to technology start-ups. In particular, the C2C online auction or intermediation market has attracted wide attention because it has made virtually every virtual user a potential firm in the sense of electronic trade. Therefore, understanding the issues in e-market structure (including the distribution and retail of online traders, market evolution patterns, and the influence of reputation system mechanism on market dynamics) helped researchers, field analysts and specialist, even policy makers identify the growth trend of the e-market, estimate the long-term impact of e-commerce on the economy, and implement effective strategies and policies in e-business operations. Initiated by Gibrat^[12] since 1931, market structure research investigates issues such as firm’s growth pattern, firm’s entry and exit, and market concentrations (Sutton, J., 1997). The research uses firm size, revenue, value added, payroll, and new capital expenditure to measure firm capacity and has reached important conclusions (Waldman, D.E., Jensen, E.J., 1998). Different from previous studies, Zh. Lin,D. Li et al. ‘s method uses reputation as the measure of firm capacity to study electronic market structure. In the business context, there are many different economic and noneconomic signals about a traditional firm’s capacity, such as marketing information, balance sheets, social responsibility, media visibility, and so on (Fombrun, C., Shanley, M., 1990). The rationale of their method is that reputation can be basically regarded as the impression and assessment of a social entity’s esteem or desirability^[13]. A social entity, either an individual or a firm, builds his or its reputation based on all past behaviors (Bromley, D.B., 1993). At a macroeconomic level, sociologists and business scholars have long recognized reputation as an indicator of collective stratification and industrial stratification^[14], which helps to categorize a person or a firm into different strata. Similarly, online reputation scoring is an index of the firm’s capacity in the online context. Following the insights provided by market structure models, their paper is intended to investigate how the distributions of online sellers’ reputation scores reflect the structure of the C2C online auction market and how the distribution changes reflect the conversion of the market status. In general, this research’s findings will shed light on understanding how the traditionally intangible reputation becomes tangible in reputation systems and plays an important role in shaping the economy in a “real” sense not only e-marketplaces.

So far, the researchers have produced exciting outcomes that validate their method. In particular, they argue that investigating the applicability of classical market structure theories to electronic markets opens the door to applying other theories from the industrial organization field to the e-market. In synthesis their work through empirical evidence provides a comprehensive analysis of the data and report relevant results. Hence it seems reasonable to look through the details of their analytical processes in order to understand the main drivers of the empirical data: in particular EBay case.

Market structure research: The research on the structure of the online C2C auction market follows the economics literature concerning market structure in light of Gibrat’s law or the law of proportional effect ( see note 11). Gibrat suggests that the expected value of the increment of a firm’s size in a period of time is proportional to the current size of the firm; in other words, firm growth rate is irrelevant to size. Applying the central limit theorem (Greene, W.H., 1993), this proposition leads to the result that the size of a firm is lognormally distributed, which is described as:

with mean

and variance

Gibrat’s law initiated an important stream of economic research that has blossomed for more than 70 years. In his extensive literature review, Sutton (1997) identifies several research string developed since Gibrat’s work. The early literature is called “growth-of-firm”—it investigates the growth pattern with regard to firm size and revenue distributions and distribution changes over time, in support of Gibrat’s law. Important research efforts in this literature include the verification of firm size growth proportionality by Kalecki (1945), stochastic modeling and public policy discussion by Simon and Bonini (1958), and multi-sectional verification of firm growth rate by Singh and Whittington in 1975. Although Gibrat’s law has provided a basis of statistical regularity for mathematical modeling in investigating the trend of market growth, studies show that Gibrat’s law is not satisfactory in explaining evidence from empirical data. Starting in the 1980s, attention was focused on econometric issues and dissatisfactions mentioned in the early literature.

Mainstream studies include those by Mansfield (1962), Hall (1987); Evans (1987), and Dunne et al.(1988). These studies mainly address firm capacity measurement with more statistical regularities, such as firm’s life cycle; formation of firm capacity distributions was extended to include consideration of effects of firm entry and exit. Mansfield finds that Gibrat’s law does not work consistently in different situations and may be interpreted in several ways, depending on how data were analyzed empirically. For example, the annual growth rates of some industries may be largely uncorrelated with prior characteristics of the firm (B.H. Hall, 1987).

The empirical studies by Evans suggest that, in many cases, the relationship between growth and firm size is not constant but rather decreasing. Hart (1995) and Oulton (1996) find that there is no significant relationship between firm size and growth when testing larger firms, and that Gibrat’s law works only when firm size is small. According to them, firm growth could be affected by some debatable shocks “that may outweigh the systematic forces that the resulting skew size distribution of firms by output will appear to be generated by a multiplicative stochastic process” (P.E. Hart, N. Oulton, 1996, pp. 1244–1245). Because the disturbance term in Gibrat’s model is assumed to be normally distributed, the final outcome is that firm size is lognormally distributed. In this sense, the work by Hart and Oulton supports Gibrat’s law with the new enhancement. Thus far, the research in market structure has enriched the understanding and application of Gibrat’s law with constant efforts from different studies. The research on market structure since the 1980s, such as the exit and entry of firms (Klepper, S., 1996), the cross-industry study of market structure, technology factors, financial constraints etc., is important in today’s e-market research because of its in-depth explanation of empirical data beyond the capability of Gibrat’s law. The authors’ work applies only a small portion of the market structure theories to examine the structure of electronic market.

Research methodology: Reputation as the indicator of online business capacity

Practically speaking, reputation scores are the only publicly accessible according to the model measures of online trader capacity in the market. For example, eBay reports a trader’s reputation in terms of several different components that reflect the seller’s behavioral performance in previous online transactions. It presumes that each individual trader, a seller in particular, is treated as a business unit or a virtual firm. A reputation score that a seller has received in a period from online C2C transactions is treated the same as the capacity of a firm. A historically accumulated reputation score reflects the status of an online trader in the market. Therefore, a seller’s reputation scores suggest his/ her relative position compared with other traders and competitors. Further, the changes in the C2C online auction market structure are accompanied and thereby influenced by the growth of different traders’ reputation scores, the entry of new traders, and the exit of existing traders. Thus, an investigation of the evolution patterns of seller’s reputation scores in the C2C online auction market aims to represent the progression of the general market structure.

It seems important to distinguish traders by their different roles: bidder in several trades, buyer because their online reputation data in different roles may have different connotations to the electronic market structure. In particular, as in EBay’s case the bidder may become a buyer or a seller after negotiation is settled: i.e only one of the bidders in an auction will become the buyer. Any bidder in one auction could be either a seller or a buyer in another. For example, in a specific auction, a bidder is just a potential buyer who may finally win the auction. In other words, the reputation distribution of bidders can mirror the reputation distribution of prospective buyers. In this work, is defined a trader as a seller when s/he sells an item in a trade, regardless of what role that person plays or will play in other trades, and is defined a trader as a buyer when he or she is bidding an item in a specific auction, regardless of whether or not that person will finally win the bid.

[...]

^[1] See http://www.forbes.com/forbes/2010/0830/entrepreneurs-groupon-facebook-twitter-next-web-phenom.html

^[2] See Michael Y. Yuan (2006), The effects of barriers to entry on monopolistic intermediary

online services: The case of a digital library, Socio-Economic Planning Sciences

^[3] In the literature eBay is being referred to as a ‘‘virtual monopoly’’; while Orbitz is feared for its potential market dominance. The European Commission has, in fact, taken the potential market dominance of OIs as a serious challenge in its competitive policy.

^[4] The described behavior differs from that of the typical monopolist, which causes under-supply of products and services. The model’s results also differ from the efficient outcome finding of standard contestable market theory; in other words, it appoints the importance of removing barriers to entry as a regulatory policy to restore efficiency in monopolistic markets.

^[5] Much of the recent literature on experience goods in relationship to the internet has centered on how information available from other consumers as well as third party reviewers can minimize the difference between experience goods and search goods. (see Bei et al. (2004)).

^[6] See, for example, Brynjolfsson and Smith (2000) and Latcovich and Smith (2001).

^[7] See Lancaster (1990) and Church and Ware (2000).

^[8] See Dayal, S., Landesberg, H., and Zeisser, M. Building trust online. McKinsey Quarterly (Oct. 2001); www.mckinseyquarterly.com/ab_g.asp?ar=1138.

^[9] See Liu, C, Marchewka, J., Lu, J., and Yu, C. Beyond concern: A privacytrust- behavioral intention model of electronic commerce. Information and Management 42, 2 (Jan. 2005), 289–304.

^[10] For a genesis research see Bakos (1997) and Lal and Sarvary (1999), also the empirical studies of Jesse W.J. Weltevreden (2006)

^[11] Jesse W.J. Weltevreden (2006) gives an example on how customers size their consuming behavior while they are in front of the choice to buy e-shopping or city centre shopping goods. He suggests there is a complementary relationship between e-shopping and city centre shopping. If this complementary relationship not proportionally related to the cost of perceived risk, then by Salam’s results we may assume that E-Shopping will gain competitive advantage (yet this is an inductive result which need to be demonstrated).

^[12] R. Gibrat, Les ine´galites e´conomiques; applications: aus ine´galite´s des richesses, a` la concentration des enterprises, aux populations des villes, aux statistiques des familles, etc., d’une loi nouvelle, la loi de l’effet proportionnel (Paris: Librairie de Recueil Sirey, 1931).

^[13] See C. Fombrun, M. Shanley, What’s in a name? reputation building and corporate strategy, Academy of Management Journal 33 (2) (1990) 233– 258

^[14] See for social stratification Fombrun, C., (1986). Structural dynamics within and between organizations, Administrative Science Quarterly 31 403– 421 ; studies regarding industrial stratification can be found in the work of Shrum, W., Wuthnow, R., (1988). Reputational status of organization in technical systems, American Journal of Sociology 9 882–912.