From infant to mother: Early disease environment and future maternal health

This paper investigates the connections between a woman's early life disease environment and her future health, socioeconomic status, and the health of her children. We exploit U.S. birth records, which can be linked to the post-neonatal mortality rates in the mother's state of birth and provide information on the outcomes of the mother and her infant. We find that exposure to disease in early childhood significantly increases the incidence of diabetes and is associated with worse socioeconomic status and maternal behaviors. We also find evidence of intergenerational transmission of maternal health shocks: among whites, higher exposure increases the probability of low birth weight infants. However, among blacks, higher maternal exposure reduces the incidence of low birth weight, possibly reflecting selection effects.     

Dem Entscheidungsverhalten auf der Spur — Was Marketing von Behavioral Economics lernen kann

Im Marketing existiert die Vorstellung, dass Kunden klare und eindeutige Produktpr?ferenzen besitzen. Neueste Forschung aus dem Bereich „Behavioral Economics“ zeigt, dass Kunden ihre Pr?ferenzen für ein Produkt in vielen F?llen erst im Rahmen der Kaufentscheidung bilden. Welche Folgen das für die Gestaltung von Marketingaktivit?ten hat, zeigt dieser Beitrag.     

Zeitliche Dynamik im Marketing: Neue Verfahren zur Auswertung

Im Marketing interessieren h?ufig Ph?nomene, die eine zeitliche Dynamik der funktionalen Zusammenh?nge aufweisen. So kann eine Werbema?nahme unmittelbar oder erst mit zeitlicher Verz?gerung wirken, wom?glich kurzfristig viel versprechend erscheinen, sich jedoch langfristig als untauglich erweisen. Linear Mixed Models (LMM) stellen ein leistungsf?higes Verfahren zur Auswertung solcher Daten dar. Anhand seiner Vorteile wird es hier vorgestellt und von der klassischen Varianzanalyse mit Messwiederholungen abgegrenzt.     

Some neglected issues in food demand analysis: retail-level demand, health information and product quality

Food demand analysis is dominated by the econometric estimation of demand systems based on aggregate market data and steady progress has been made in analytical techniques. Yet some issues have been neglected in food demand analysis which are crucial for understanding recent consumption trends in industrialised countries. Three of these issues are dealt with here: analysis of food demand at the retail level; influence of health information on food demand; and importance of product quality for food demand. It is shown that answers to important questions in these areas can be given when large and unconventional data sets are used.     

The Dynamics of Pest Resistance Management: The Case of Refuge Fields for Bt Crops

We examine the optimal time‐variant refuge policy to manage pest resistance to Bacillus thuringiensis (Bt) crops in a finite, discrete‐time horizon model. We identify analytically the intertemporal effects of refuge fields on the pest population and its susceptibility. The shape of the optimal refuge policy and whether or not pest susceptibility should be exhausted completely at the end of the time horizon depend crucially on the values of a cost premium of Bt seeds and the fitness cost of resistance (over mortality of resistant pests) and are addressed via numerical simulations. We demonstrate the importance of modeling the dynamics of the biological system accurately, of defining a diploid (and not haploid) biological model, and of using a discrete‐time (rather than continuous‐time) framework.     

Should You Really Produce What Consumers Like Online? Empirical Evidence for Reciprocal Voting in Open Innovation Contests

In open innovation, firms increasingly rely on online consumer votes to evaluate ideas for new products and services. Votes can represent cost‐effective external information about idea quality that can inform and facilitate a firm's task of evaluating and screening of ideas at the early stages of the innovation process. Challenging this perception, we proposed that consumer votes provided in open innovation contests can be socially biased by reciprocal voting. On the basis of theories related to cooperation and social influence, we argued that both gregarious consumers (those who solicit social ties) and consumers who initiate direct reciprocity (those who vote for others) signal a willingness to cooperate that stimulates reciprocal voting from peers. We empirically investigated consumer voting behavior using a unique dataset with information obtained from actual open innovation contests in which consumers could submit their own ideas and see and vote for the ideas of others. We found that both gregariousness and the initiation of direct reciprocity positively influence votes received. Such cooperation pays off for consumers because firms indeed use votes to inform internal idea evaluations. We also found, however, that the votes an idea receives during an innovation contest cannot significantly explain its later revealed quality. Reciprocity may be an effective form of cooperation among consumers, but it has potentially negative implications for firms' evaluations. Our results also indicated that beyond reciprocity, consumers and firms value different types of ideas, which further differentiates their evaluations. Thus, firms should not only be aware of social biases in votes but also account for the diverging idea preferences of customers.     

A web-based multi-agent decision support system for a city-oriented management of cruise arrivals

Cruise tourism represents a strategic sector for the economic growth of several countries, impacting on different direct and indirect markets. The arrival of cruises in a city represents an unmissable opportunity to increment its tourist market penetration. Nevertheless, the management of an unforeseen number of passengers that need to visit a city in a short time may also have a negative impact, so reducing the expected benefits. This is mainly due to the difficulty of taking the right decisions when organizing the dispatching of passengers in different city areas since these decisions depend on several conditions that can also dynamically occur, and may have an impact on different city sectors. Here, a decision support system is proposed to help involved stakeholders to make decisions to plan passengers' transportation in the city and also to evaluate the consequences for the city if the plans are really implemented. The system is designed according to the multi-agent paradigm, so allowing one to easily manage the necessary coordination among different entities and data sources that are usually distributed and need to cooperate to provide useful suggestions. In addition, a prototype of a web-based application is provided to end users, so that it can run on heterogeneous platforms, and it can be easily accessed by different users from different devices, as it is the case for the considered application domain.