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Consumer Claims to Space in the Politics of Consumer Identity
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Perhaps the most popular topic with respect to the potential impact of artificial intelligence (AI) concerns what this technology means for jobs. As AI develops and mimics increasing levels of cognitive functions, the scope of jobs that might be impacted is great. This has motivated investigations into the nature of cognitive skills required for a wide array of occupations in order to identify those most likely to be impacted. Estimating the impact of AI on labor market outcomes requires an understanding of the particular tasks that AI will directly effect. Our goal in this article is to specify the characteristics of the technological change brought about by AI, and then to demonstrate how understanding these details provides useful insight into the labor market consequences.
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Paying for a Chance to Save Money: Two-Part Tariffs in Name-Your-Own-Price Markets
Image AddedRobert Zeithammer, Professor, Anderson School of Management, University of California - Los Angeles
Synopses
Prior theoretical research has shown that a Name-Your-Own-Price (NYOP) seller can profit from charging each prospective buyer a non-refundable fee for the opportunity to place a bid, akin to an entry fee to the seller’s store. We examine the profitability of such two-part tariffs in NYOP markets using incentive-compatible laboratory experiments. Overall, our results suggest two-part tariffs increase NYOP profit in a standard information-poor setting in the short run, but they are not as profitable as theory would suggest when the bidders get more information or experience. We also propose an individual-level non parametric test of the risk-averse expected utility model, and the test results suggest that this canonical model for decision making under uncertainty is not a good fit to the behavior of a substantial proportion of our subjects.