Joost M.E. Pennings

Smart Shopping Carts: How Real-Time Feedback Influences Spending

Although interest in smart shopping carts is increasing, both retailers and consumer groups have concerns about how real-time spending feedback will influence shopping behavior. Building on budgeting and spending theories, the authors conduct three lab and grocery store experiments that robustly show that real-time spending feedback has a diverging impact on spending depending on whether a person is budget constrained (“budget” shoppers) or not (“nonbudget” shoppers). Real-time spending feedback stimulates budget shoppers to spend more (by buying more national brands). In contrast, this feedback leads nonbudget shoppers to spend less (by replacing national brands with store brands). Furthermore, smart shopping carts increase repatronage intentions for budget shoppers while keeping them stable for nonbudget shoppers. These findings underscore fundamental unexplored differences between budget and nonbudget shoppers. Moreover, they have key implications for both brick-and-mortar and online retailers as well as app developers.

How Investor Perceptions Drive Actual Trading and Risk-Taking Behavior

Recent work in behavioral finance showed how investors’ perceptions (i.e., return expectations, risk tolerance, and risk perception) affect hypothetical trading and risk-taking behavior. However, are such perceptions also capable of explaining actual trading and risk-taking behavior? To answer this question, we combine monthly survey data with matching brokerage records to construct a panel data set allowing us to simultaneously examine investor perceptions and behavior. We find that investor perceptions and changes therein are important drivers of actual trading and risk-taking behavior: Investors with higher levels of and upward revisions of return expectations are more likely to trade, have higher turnover, trade larger amounts per transaction, and are more likely to use derivatives. Investors with higher levels of and upward revisions in risk tolerance are more likely to trade, have higher buy-sell ratios, use limit orders more frequently, and hold riskier portfolios. Investors with higher levels of risk perception are more likely to trade, have higher turnover, have lower buy-sell ratios, and hold riskier portfolios.

State of the art in benefit-risk analysis: economics and marketing-finance.

All market participants (e.g., investors, producers, consumers) accept a certain level of risk as necessary to achieve certain benefits. There are many types of risk including price, production, financial, institutional, and individual human risks. All these risks should be effectively managed in order to derive the utmost of benefits and avoid disruption and/or catastrophic economic consequences for the food industry. The identification, analysis, determination, and understanding of the benefit-risk trade-offs of market participants in the food markets may help policy makers, financial analysts and marketers to make well-informed and effective corporate investment strategies in order to deal with highly uncertain and risky situations. In this paper, we discuss the role that benefits and risks play in the formation of the decision-making process of market-participants, who are engaged in the upstream and downstream stages of the food supply chain. In addition, we review the most common approaches (expected utility model and psychometrics) for measuring benefit-risk trade-offs in the economics and marketing-finance literature, and different factors that may affect the economic behaviour in the light of benefit-risk analyses. Building on the findings of our review, we introduce a conceptual framework to study the benefit-risk behaviour of market participants. Specifically, we suggest the decoupling of benefits and risks into the separate components of utilitarian benefits, hedonic benefits, and risk attitude and risk perception, respectively. Predicting and explaining how market participants in the food industry form their overall attitude in light of benefit-risk trade-offs may be critical for policy-makers and managers who need to understand the drivers of the economic behaviour of market participants with respect to production, marketing and consumption of food products.

Graphical Illustration of Interaction Effects in Binary Choice Models: A Note

Graphing procedures for evaluating power or interaction terms in binary logit and probit models are illustrated in an application to hog producers decisions based on transaction cost economics hypothesised positive effect of the interaction of uncertainty and asset specificity on contract use. Results support the hypothesis, particularly for producers that are otherwise on the cusp (near the 50/50 probability) of choosing either contract or spot transactions based on their responses for other variables. Such insights may not be drawn without use of the demonstrated graphing procedures.