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Reputation Effects In Peer-To-Peer Online Markets
A reputation effect in peer-to-peer online markets study analyzes the relationship between online markets and reputation systems. The system allows traders to comment on the behavior of each other and their attributes through ratings and text messages. The ratings given account for the seller’s reputations signaling their trustworthiness and competence. The reputation effect was drawn from a theoretic game framework, and statistical analysis was used to correlate results from several studies involved in research for the same topic.
A Critique of the Research Article’s Analysis Section
The researchers used quantitative data, which is the most appropriate one for the study. This is because, the study compares seller reputation which is measured by their ratings and their performances measured by final commodity prices. Ratings and prices can only be expressed in numerical figures (Snijders & Matzat, 2019). Secondly, the researchers analyzed the data statistically using statistical models including the Pearson correlation coefficient model and multiple linear regression coefficients model. Then, the obtained data were presented comprehensively using figures and tables, making understanding of the analyses less complex.
A Critique of the Results Section
The result conclusions are logical because they stress the significance of seller reputation in promoting buyer trust. This makes sense because most people buy commodities from the sellers they know and trust to provide them with genuine products. On the other hand, a seller with a damaged reputation scares off the buyers (Lindenberg et al., 2020). Implications for further research are included because results show a correlation between seller reputation and their performance, whereby positive ratings imply better performance and negative ones mean poor performance.
The implications are relevant to the current study because they showcase the importance of sellers having a positive image to build buyer trust. Also, they are appropriate for furthering literature since past studies concerning the topic present incoherent results leading to disagreements on seller reputation’s meaning and how substantial it is (Snijders & Matzat, 2019). This makes it a bit complex to interpret the reputation effect with seller performances in the market.
I believe this study qualifies to be the primary data source for the investigation of the relationship between the reputation of the seller and their performance in the market. I would recommend this article for all business individuals to shed light on how their reputation impacts their businesses. It can help many business people change their attitude and build their reputation to gain customer trust.
References
Lindenberg, S., Wittek, R., & Giardini, F. (2020). 6. Reputation effects, Embeddedness, and Granovetter’s error.Advances in the Sociology of Trust and Cooperation, 113-140. Web.
Snijders, C., & Matzat, U. (2019). Online reputation systems. The Oxford Handbook of Gossip and Reputation, 478-495. Web.
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