Reputation and uncertainty in online markets


One of the main problems which occurs in electronic markets is the information asymmetry between buyers and sellers. Buyers do not have the same information about the products as sellers do. The most important part of information advantage sellers have, has to do with the quality of the product. Sellers know the real quality, while buyers must rely on the description text provided by the seller. A well-known concept in the context of information asymmetry is moral hazard, which occurs when one party carries more risk than the other party. This happens in electronic markets when the buyer needs to complete the payment before the seller sends the product. In this way, the seller carries more risk. One of the most common types of internet fraud has to do with non-existing sellers or sellers who deliver unrepresented goods or even no goods at all. One way to overcome this information asymmetry is to build a relation with the other party. The problem is that for offline transactions this seems to be feasible, but for online transactions building a relationship seems to be harder. Therefore, the online reputation systems are introduced. In this way buyers can rate the behavior of the sellers, so that the more reliable sellers stand out against the unreliable sellers. Rating sellers may help other buyers in their decision process, so the online reputation system is a good example of consumer value creation.

In the article by Rice (2012) reputation and uncertainty in online markets are tested in a game setting. The game setting is as follows:

Game sequence

In this game setting there are two groups: buyers and sellers. Buyers have an amount of money which they ‘invest’ in the seller. The seller decides on how much of that investment he will return. Therefore the ‘investment’ can be seen as a price, and the ‘return’ can be seen as a delivered good. Initially the sellers announces how much he will return (e.g. quality of a good). Then, the buyer chooses how much he wants to invest in the seller (e.g. how much does the buyer wants to pay for the product). After that, the seller chooses how much of that money which was invested by the buyer he will return to the buyer (e.g. what quality will he deliver). Finally, the buyer has the opportunity to rate the seller. There is also an uncertainty factor included in the game setting. This provides the uncertainty that the returned amount can be intercepted by the researchers with a chance of 30%. The findings suggest that the occurrence of reputation systems stimulates people to take part in a transaction. Buyers who don’t meet expectations receive poorer ratings, while buyers who exceed expectations receive higher ratings. But when the buyers doubt whether the unmeet expectations are not caused by the seller, fewer poor ratings occur. This is related to the uncertainty factor. It seems that the higher the uncertainty factor, the more the buyers tend to trust the other party. Also, sellers’ positive ratings result in a higher investment of buyers. In some cases, a poor rating is weighted more heavily than a good rating.

I think the article highlights some very interesting aspects of online reputation systems, but I still have one question on my mind after reading this article. Nowadays, a lot of these online reputation systems are extended with visual text instead of just a scale rating. These text boxes mostly have much more details about the transaction experience with a specific seller and have therefore more value. I am wondering whether the findings of this article are also relevant in reputation systems with boxes of text, because these text-based reputation systems seemed to be more popular in the recent years. What do you think?

Sources:

Sarah C. Rice, (2012) Reputation and Uncertainty in Online Markets: An Experimental Study. Information Systems Research. 23(2):436-452.

http://www.scambusters.org/topscams2013-14.html, retrieved 22 April, 2015

http://www.spamlaws.com/internet-fraud-stats.html, retrieved 22 April, 2015

Co-Creation with Food Allergies


Many people have developed an allergy for some certain food. It looks like some kind of trend nowadays; a lot of people are deleting some ingredients in their daily meals. Some people are just trying a new diet, hoping they will lose weight. But the amount of people who really have an allergy is high. It is very difficult for those people to control what they eat. When they cook themselves they can easily check all the ingredients. Therefore it is really difficult for them to eat in a restaurant, because they have no control. Those restaurants also want to satisfy their customers, they are also concerned with corporate social responsibility (CSR). There must become accessible information for the restaurant about how to respond on those particular customers. The main problem is the lack of information of the employees. Most of the time the employees do not know which ingredients are in the dishes. Sometimes, they do not want to admit this and as a result they do give a wrong advice. Second, the employees are somewhat uncertain about the ingredients, and they will ask the cook. They come back and look at least as uncertain as before, this affects the customer. The customer will become even more insecure, because no know really knows if it will cause damage, as it happens an allergic reaction.

Restaurants need to deal with this issue. This has influence on the entire business, the menu formulations, and the methods of obtaining ingredients, maintenance of the ingredients’ information, employee training, cooking and storage. It is about the whole design until the meal is places on the table. The process must become easier for the restaurant as well as for the customer. Therefore they need mobile devices, like an smartphone or an tablet. This can be installed as an app on the customers’ device or an mobile device owned by the restaurant. The customer can see which dishes are appropriate for him/her and the cook can see this easily. Even when there are some questions or uncertainties, the chef can quickly asks the customer to clarify. There is no need for an intervening employee, but when the app is explicit there is not even need for questions. The customer can also identify the amount of certain herbs and spices is allowed. The customer can give feedback and help develop the app. When a customer identifies the personal allergy, it can indicate what is related to this allergy. When there are more customers, it will become some sort of a database that is easy and quick to access for restaurant(s). This needs some extra money to invest in the mobile devices for the restaurants. But this will be paid back finally. Customers with allergies will be able to dine out in nice restaurants. They will not be alone but bring – most of the time – at least one person with them, therefore a double win-win for the restaurant!

Sources

  • Khosrow-Pour, M. (2014). Inventive Approaches for Technology Integration and Information Resources Management. IGI Global. 317-332
  • Robert J. Harrington , Michael C. Ottenbacher & Kelly A. Way (2013) QSR Choice: Key Restaurant Attributes and the Roles of Gender, Age and Dining Frequency, Journal of Quality Assurance in Hospitality & Tourism, 14:1, 81-100
  • http://www.foodallergy.org/facts-and-stats