We correlate competitive bidding and profits in symmetric independent private value first-price auctions with salivary testosterone, estradiol, progesterone, and cortisol in more than 200 subjects. Bids are significantly positively correlated and profits are significantly negatively correlated with basal salivary progesterone, but only for females who do not use hormonal contraceptives. Surprisingly, we have null findings for basal testosterone, estradiol, and cortisol for both males and females. We show that our finding for progesterone is not mediated by risk aversion or bidding mistakes. No hormone responds to total profits in the auctions except for a small positive response of the stress hormone cortisol in males. Data, as supplemental material, are available at http://dx.doi.org/10.1287/mnsc.2014.1959 . This paper was accepted by Uri Gneezy, behavioral economics.

This paper examines how firm investments in technology-based employee monitoring impact both misconduct and productivity. We use unique and detailed theft and sales data from 392 restaurant locations from five firms that adopt a theft monitoring information technology (IT) product. We use difference-in-differences models with staggered adoption dates to estimate the treatment effect of IT monitoring on theft and productivity. We find significant treatment effects in reduced theft and improved productivity that appear to be primarily driven by changed worker behavior rather than worker turnover. We examine four mechanisms that may drive this productivity result: economic and cognitive multitasking, fairness-based motivation, and perceived increases of general oversight. The observed productivity results represent substantial financial benefits to both firms and the legitimate tip-based earnings of workers. Our results suggest that employee misconduct is not solely a function of individual differences in ethics or morality, but can also be influenced by managerial policies that can benefit both firms and employees. This paper was accepted by Serguei Netessine, operations management.

In a procurement context, it can be quite costly for a buyer when the winning seller underestimates the cost of a project and then defaults on the project midway through completion. The average bid auction is one mechanism intended to help address this problem. This format involves awarding the contract to the bidder who has bid closest to the average of the bids submitted. We compare the performance of this mechanism with the standard low price mechanism to determine how successful the average bid format is in preventing bidder losses as well as its impact on the price paid by the buyer. We find the average bid mechanism to be more successful than expected because, surprisingly, bidding behavior remains similar between the average bid and low price auctions. We provide an explanation for the bidding behavior in the average bid auction that is based on subjects having problems processing signals near the extremes of the distribution. This paper was accepted by Teck-Hua Ho, behavioral economics.

Modeling consumer heterogeneity helps practitioners understand market structures and devise effective marketing strategies. In this research we study finite mixture specifications for modeling consumer heterogeneity where each regression coefficient has its own finite mixture—that is, an attribute finite mixture model. An important challenge of such an approach to modeling heterogeneity lies in its estimation. A proposed Bayesian estimation approach, based on recent advances in reversible-jump Markov chain Monte Carlo methods, can estimate parameters for the attribute-based finite mixture model, assuming that the number of components for each finite mixture is a discrete random variable. An attribute specification has several advantages over traditional, vector-based, finite mixture specifications; specifically, the attribute mixture model offers a more appropriate aggregation of information than does the vector specification facilitating estimation. In an extensive simulation study and an empirical application, we show that the attribute model can recover complex heterogeneity structures, making it dominant over traditional (vector) finite mixture regression models and a strong contender compared to mixture-of-normals models for modeling heterogeneity. This paper was accepted by Pradeep Chintagunta, marketing.

Examining changes in two different retail formats, we show that consumers alter their purchases depending on the retail environment. In both settings, the change in behavior coincides with a reduction in the interpersonal interaction required to complete a transaction. As such, we contend that the format changes reduced a “social friction” that would otherwise inhibit consumers due to an implicit cost associated with ordering certain items in social settings. This paper was accepted by Pradeep Chintagunta, marketing.

If the price of a stock differs from its intrinsic value by a random noise, then value stocks are more likely to have negative noise; they are thus more likely undervalued and have higher expected return than justified by risk. The same intuition applies to small capitalization stocks. We formally verify and explore this intuition by using a standard noise-in-price model. This intuition is different from the Jensen’s inequality effect studied by Blume and Stambaugh [Blume ME, Stambaugh RF (1983) Biases in computed returns: An application to the size effect. J. Financial Econom. 12(3):387–404]. Our model is parsimonious: the value premium as well as size premium are computed in closed form and depend on only four parameters: mean of stock return, volatility of stock return, volatility of the price-to-dividend ratio, and noise volatility. We emphasize that only a moderate volatility of price noise is needed to generate the observed value premium. However, the model cannot generate the observed size premium. This paper was accepted by Wei Jiang, finance.