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.     

The price of sanctions: An empirical analysis of German export losses due to the Russian agricultural ban

The aim of this paper is to contribute to the vivid political discussion on the consequences of the Russian agricultural import ban on the German export market by quantifying export losses that German agri-food exporters encountered on the Russian market due to the agricultural import ban of 2014. A gravity-type approach is used to measure the sanction effect in a panel of German agri-food exports covering the period from January 1999 to June 2018. The ban effect is disentangled from a sequence of different geopolitically- and economically driven episodes. Once macroeconomic developments of the Russian economy as well as individual stages of decreasing trade cooperation in the preban period are accounted for, the import ban reduced German agri-food exports significantly but was not the major cause. Therefore, a simple elimination of the ban will not be enough to restore trade to the presanctions level.     

New Perspectives on Customer Relationships: How Relational Models Influence Customer Experience and How They Are Activated

Abstract

Much research has been conducted into the determinants of customer experience. However, these studies do not include relationship norms as a possible determinant of customer experience. Nevertheless, there are strong indications that the relationship norms used by a customer are an important factor in customer behavior and customer experience. The purpose of this paper is to investigate the influence of relational models on customer experience and to explain possible differences in presence of relational models. This paper describes the results of two studies. The first study focuses on the effects of relational models on customer experience. This first study shows that the type of relationship has a strong influence on customer experience in terms of consumption emotions, customer satisfaction, and recommendation intention. Knowing that differences in the presence of relational models have a strong influence on customer experience, a second study focuses on finding a possible explanation for the differences in the presence of relational models. We hypothesize that differences in the presence of relational models can be explained by how organizations approach their customers and how customers perceive the organization. Especially, the perceived organizational involvement and freedom of choice as perceived by the customer play an important role. The second study, therefore, focuses on the influence of perceived organizational involvement and freedom of choice on relational models. The study shows that organizational involvement and freedom of choice have a significant impact on the activation of relational models. The findings are interesting for organizations that want to improve customer experience.