Reputation and Uncertainty in Online Markets: An Experimental Study

Abstract

T his paper employs a modified investment game to study how online reputation ratings are assigned, and thus how electronic reputations are formed in transactions where buyers and sellers interact anonymously. Of particular interest are the important questions of how online reputations evolve and how specific reputation information is interpreted by market participants. We vary the level of uncertainty in the transaction environment, and measure the effects of this manipulation on buyers' trust and their subsequent rating behaviors. We distinguish between a reputation mechanism and specific reputation information, finding the former has an association with the overall decision of whether to transact in the marketplace, while the latter shows significance in purchase decisions regarding specific sellers. We also find that aggregate reputation information is weighted differently than singular reputation information. Finally, we show that when reputations are increasingly noisy, buyers are less likely to react negatively to poor ratings and are more likely to give sellers the benefit of the doubt when seemingly uncooperative outcomes occur.

Hidden semi-Markov model-based reputation management system for online to offline (O2O) e-commerce markets

“…ACCEPTED MANUSCRIPT 4 product/service quality may be affected. This implies that an offline merchant may not be able to provide consumers with products/services that are consistent with those claimed online.…”

“…In addition, it also discusses some extant reputation management systems used by eBay [17,18], Amazon [19,20] and Alibaba [21]. More information about this research type can be found in [3,4,6,22,23]. Research type 4 in Figure 1 mainly concentrates on new reputation management problems that stem from online to offline channels.…”

“…from online consumers, offline merchants and authoritative third parties are first collected by "customers' information management" (P1) and the "offline merchants and third party information management" (P2) before being stored in D1-D3. 4 Next, data flows from D1, D2 and D3 are processed by the "reputation-related data-preprocessing" procedure (P3). The processed data are stored in D4 and can be directly used by the "HSMM-based reputation management" (P4).…”

“…and B2B), reputation management has become one of the critical factors that restrict their development [2][3][4], and this is also no exception to the O2O e-commerce model.…”

The economy of attention in the age of (mis)information

“…Reputation systems are used to collect and analyze information about the performance of service entities with the purpose of computing reputation scores for service objects and service entities. A fundamental assumption of reputation systems is that reputation scores can help predict the future performance of the respective entities and thereby reduce uncertainty of relying parties during the decision making processes [1][2][3][4][5][6].…”