No abstract

This study of the influence of the marketing department (MD), as well as its relationship with firm performance, includes seven industrialized countries and aims to generalize the conceptual model presented by Verhoef and Leeflang (2009). This investigation considers the antecedents of perceived MD influence, top management respect for the MD, and MD decision influence, as well as the relationships of these three influence variables with market orientation (MO) and business performance (BP). Meta-analytic procedures reveal initial empirical generalizations: Accountability, MD innovativeness, and the customer connection capabilities of the MD relate consistently to all three studied MD influence measures. The generalization also shows that MD influence contributes to BP indirectly through its positive relationship with MO and directly through its positive direct relationship with BP.

Abundant evidence exists that expected utility theory does not adequately describe decision making under risk. Although prospect theory is a popular alternative, it is rarely applied in strategic situations in which risk arises through individual interactions. This study fills this research gap by incorporating prospect theory preferences into a dynamic game theoretic model. Using a large field data set from multiple online pay-per-bid auction sites, the authors empirically show that their proposed model with prospect theory preferences makes a better out-of-sample prediction than a corresponding expected utility model. Prospect theory also provides a unified explanation for two behavioral anomalies: average auctioneer revenues above current retail prices and the sunk cost fallacy. The empirical results indicate that bidders are loss averse and overweight small probabilities, such that the expected revenue of the auction exceeds the current retail price by 25.46%. The authors illustrate and empirically confirm a managerial implication for how an auctioneer can increase revenue by changing the details of the auction design.

Linear regression analysis is one of the most important statistical methods. It examines the linear relationship between a metric-scaled dependent variable (also called endogenous, explained, response, or predicted variable) and one or more metric-scaled independent variables (also called exogenous, explanatory, control, or predictor variable). We illustrate how regression analysis work and how it supports marketing decisions, e.g., the derivation of an optimal marketing mix. We also outline how to use linear regression analysis to estimate nonlinear functions such as a multiplicative sales response function. Furthermore, we show how to use the results of a regression to calculate elasticities and to identify outliers and discuss in details the problems that occur in case of autocorrelation, multicollinearity and heteroscedasticity. We use a numerical example to illustrate in detail all calculations and use this numerical example to outline the problems that occur in case of endogeneity.

The ability to calculate and understand the profitability of deal-of-the-day promotions (DoDs) is of vital importance for merchants. It is also challenging because it requires these merchants to consider long-term, cross-selling, and cannibalization effects and select an appropriate discount for the promotion. The authors develop and implement a model as a free online calculator ( http://www.coupon-calculator.com ) to help merchants to determine the profit they can generate from these promotions. This calculator evaluated almost 3,700 DoDs from the merchants’ and providers’ perspectives. To gain insight on the expected profitability of DoDs, the authors analyzed 627 of these planned promotions and 30 realized promotions. The results indicate that two-thirds of the planned and all realized DoDs are expected to be profitable in the long term. Yet, DoDs are unlikely to pay off in the short term. The findings also show that unredeemed coupons strongly increase profit, particularly those of the provider.