Conclusions
The conclusion seems incomplete as negative ratings of online sellers would need to strongly correlate with low bidding to make adverse selection completely proven in this study. The fact that there is no strong correlation in this study to negative rankings, a foundational element of asymmetric information, makes one see the research as incomplete in its design.
Selection of Independent and Dependent Variables
The research design is incomplete in that it does not capture sales lost due to prices being too high and statistically proving the full hypothesis of adverse selection. The selection of the studies' independent variables quantified and validates high trust emanating from proven reputation systems. It does not however show the full elasticity of adverse selection on the price bands of cars sold on Ebay Motors. There is no demand curve, and further, no demand variable captured in this analysis, making elasticity of demand impossible to measure. Without that, the full impact of adverse selection cannot fully be explained.
Refuting an Online Auction Adverse Selection Hypothesis
As the research from Wolf and Muhanna (2005) shows, there are statistically significant results highlighting the effectiveness of online auto auction sites using warranties and reputation systems that validate a seller's reliability,...
This quantifying of trust auto correlates to the statistically significant scores for reputations of online sellers and validates the researcher's findings on this hypothesis. What is missing however is the statistical significance of negative scores for sellers who rely on auto auctions and in practicing the advantages of asymmetry of information, financially gain at the expense of imperfect information. Ironically, one could argue, for adverse selection to actually be true in both upward- and downward-sloping pricing in auto markets dominated by asymmetrical information, negative ratings would need to be statistically significant. In a very ironic sense, the study by Wolf and Muhanna (2005) validate that asymmetry of information benefits those sellers who are transparent, earn trust and therefore high reputation scores. Missing from Wolf and Muhanna (2005) work is the complete validation of the adverse selection dynamics those authors claim.
Selecting the right vendor (background check) Choosing the right vendor can be just as important as the system being setup and the software being utilized. Choosing the right vendor is just as important as choosing the right EMR software. Daniel Ray, in the article, "Electronic Medical Records (EMR) Vendors- Points to Consider," declares the following things are essential in choosing the right vendor for your business: 1. Checking the track record: evaluate
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