Money is much more than dollars, pounds or yen. The digitization of money has led to the emergence of numerous virtual currencies (i.e., company-issued currencies for purchases within the company’s ecosystem). Billions of US dollars are exchanged using such virtual currencies every year. Still, most pricing-related research focuses on payments using official currencies. In our article, we build upon payment mechanism and processing fluency research to predict consumers’ purchase intentions with virtual currencies. Study 1 addresses how perceived money similarity can be predicted by semantic similarity measurements. In Studies 2 and 3, we replicate real-world purchase scenarios to show how a virtual currency’s dissimilarity to money decreases purchase intentions through both the decrease of processing fluency and the increase of pain of payment. Managerial as well as theoretical implications are discussed.

Money is much more than dollars, pounds or yen. The digitization of money has led to the emergence of numerous virtual currencies. Countless virtual currencies have emerged through the digitization of money. Billions of U.S. dollars are exchanged using such virtual currencies every year. Still, most pricing-related marketing research focuses on payments using official currencies. In our article, we build upon payment-mechanism and processing fluency research to predict consumers’ purchase intentions with virtual currencies. Study 1 addresses how perceived money similarity can be predicted by semantic similarity measurements. In Studies 2 and 3, we replicate real-world purchase scenarios to show how a virtual currency’s dissimilarity to money decreases purchase intentions through both the increase of processing fluency and the increase of pain of payment. Managerial as well as theoretical implications are discussed.

While inspiration plays an essential role in everyday consumer language and marketing practice, practitioners often lack a clear understanding of the drivers of inspiration. Scientifically, inspiration challenges established categorizations as it combines cognitive and motivational aspects of human behavior. By integrating inspiration with goal systems theory, this paper proposes a framework for the psychological processes which drive inspiration in marketing. Across three experimental studies, we test the ability of a goal-systemic perspective to predict effects on inspiration. Study 1 reveals that inspiration can result both from the addition of new means as well as new goals and depends on participants' pre-existing goal-systems. Study 2 replicates these findings and shows that the effects on inspiration are largely mediated by the strength of new goal-means associations. Finally, study 3 explores the effect of participants' mindsets on inspiration through new goals and means. Overall, these results provide evidence that the effects of realizing new goals and new means on inspiration depend on pre-existing goal systems and mindsets in a way that is consistent with goal systems theory. Therefore, goal systems theory can provide a useful framework for the analysis of inspiration in consumer research.

Companies increasingly use open innovation and co-creation processes on the Internet. Despite this rising trend in management, the different forms of open innovation on the Internet have only scarcely been investigated from a macroperspective that systematically categorizes customer-supplier interactions based on a conceptual framework. Using a cross-case study design, we characterize and differentiate six types of customer-supplier processes on the Internet regarding underlying value propositions, value network configurations, and modes of interaction. These co-creation processes can be categorized according to their value propositions that follow different stages of the consumption circle. Each value proposition, as a cohesive element, determines a different value network configuration. We examine how network leaders create different modes of interactions in these value networks that we analyze regarding power, relationship, and coordination mechanisms. Across cases, open innovation on the Internet changes the architecture of the value chain from a single-directed stream to a loop of knowledge exchange that includes almost every vertical stage. Companies therefore cannot assign customer input to a certain functionality but rather must decipher it through interdisciplinary approaches that involve the cooperation of multiple areas. The macro-perspective framework can help companies to identify in which areas they can use open innovation and how to establish co-creation processes in the newly evolving value networks.

The unprecedented diversity of marketing tools available in e-commerce increasingly poses fundamental challenges to marketing practitioners and researchers. New types of marketing tools have emerged at rapid pace. Yet, due to the lack of overview, harnessing the potential of these new marketing opportunities is challenging. Similarly, marketing research is handicapped by the lack of an integrative conceptual framework. In response to this void, we develop a up-to-date taxonomy of marketing instruments in e-commerce. Based on a comprehensive compendium of marketing tools currently available to e-commerce businesses, we empirically and intersubjectively develop an integrative framework using the open card sort method. We identify 10 marketing instrument categories covering 62 marketing tools. Our results provide a valuable resource for marketing strategy development and an evidence-based framework for future research.

For more than 30 years, shopping motivation has remained a current topic, discussed in leading academic journals (see, e.g., Tauber 1972, Cox et al. 2005). Moreover, since different retail strategies correspond to varying shopping motives (Gröppel-Klein 1998), research in this area has been ascribed considerable potential to generate meaningful managerial implications (Keng and Ehrenberg 1984). Given the long-enduring scholarly efforts to explain consumers' shopping motivation, it comes as a surprise that empirical studies commonly simplify different motives in that they are not classified as belonging to specific degrees of abstraction or hierarchical levels of specificity (see DeVellis 2003). Yet, conceptual work has introduced the hierarchical dimension of consumer shopping motivation to the academic discourse (see, e.g., Rudolph et al. 2004). In particular, scholars such as Mooradian and Olver (1996) point out that consumers' shopping motives "can be organized hierarchically with broad higher-order motives encompassing multiple specific motives" (p. 587-588). This hierarchical perspective seems logical in that "a single shopping behavior enables individuals to acquire a set of hierarchically arranged benefits which can include cognitive, emotional, experiential, sensory, affiliative, and material benefits" (Darden and Dorsch 1990, p. 301). However, whereas research in the areas of general psychology (see, e.g., Rifkin 1985) and organizational behavior (see, e.g., Cropanzano et al. 1993) has long recognized and investigated the hierarchical nature of human motivation, this phenomenon has been widely ignored in the literature on shopping behavior. To the authors' best knowledge, there is no published empirical research that investigates consumers' shopping motivation from a hierarchical perspective. This shortcoming surprises in particular as among today's scholars it seems "generally accepted that consumer behavior is goal-oriented, and that goals at different levels of abstraction are hierarchically related" (Warlop et al. 2000, p. 203). The present research takes first empirical steps towards the development of a hierarchical theory of shopping motivation. In this view, we "think of goal-directed behavior in terms of a hierarchical model of action and [...] make specific suggestions as to what the levels in the hierarchy might be" (Pieters et al. 2001, p. 416). As recommended by Mitchell (2001) as well as McGoldrick (2002) the theory of means-end chains is adopted to investigate consumer shopping motivation under different degrees of abstraction. The means-end approach seems appropriate since its strength lies in revealing the causal relationships among different theoretical stages of motivation (Bagozzi and Edwards 1996), thereby facilitating an "in-depths redefinition of the concepts and hypotheses relevant to a problem" (Laurent and Pras 1999, p. 253). A four-level framework by Olson and Reynolds (2001) was adopted, differentiating among attributes, functional consequences, psychosocial consequences, and personal values. From this motivational perspective on means-end chains, the elements of the framework can be regarded as "motivational layers" (Cohen and Warlop 2001, p. 404) whereby the relationships among them express the underlying reasons why certain attributes or consequences are desired by the consumers (Reynolds and Gutman 2001). Data was collected by means of 40 in-depth interviews with retail customers inside store facilities, referring to the context of apparel shopping. During the interview procedure, relevant store attributes were elicited using Breivik and Supphellen's (2003) technique of ideal description, followed by a series of subsequent questions based on the laddering guidelines by Reynolds and Gutman (2001). Consumer responses were content-analyzed, summarized in an implication matrix, and depicted in three hierarchical value maps. As a key finding, four motivational patterns represent shoppers' predominant cognitive driving forces in apparel shopping, namely, shopping pleasure, frictionless shopping, quality seeking, and value seeking. In particular, however, the current research underscores that a unique advantage of the means-end chain methodology consists of relating consumer motivation directly to its corresponding attribute preference. That is, the relationship between specifically desired characteristics of retail stores and underlying motivations are revealed, thereby reducing the shortcoming of current motivational theories to "account for specific actions and to point to particular strategies for influencing behavior" (Bagozzi et al. 2003, p. 915-916). Accordingly, the findings of this work may provide first insights to align retail marketing strategies with shoppers' underlying motivations in addition to stimulating the development of a comprehensive hierarchical theory of shopping motivation.

This study examines the performance implications of the world's leading retailers' assortment diversification behavior over thirteen years (from 1997 to 2009). Results show that assortment diversification into food and non-food retailing increases retailers' sales, while it decreases their profits. Thus, our findings indicate that retailers' decision to diversify across food and non-food assortments results in a trade-off between the objectives of market-based (i.e., sales) and accounting-based (i.e., profits) performance maximization. Moreover, beside the negative effect of assortment diversification on profits, we find suggestive evidence that retailers can decrease the volatility of their profits by diversifying into food and non-food assortments

New technologies, such as autonomous smart-home devices and consumer goods subscriptions, allow for the automation of consumers’ shopping. When using autonomous commerce, consumers practically outsource their decision making, whereby it is machines or firms making purchase decisions on consumers’ behalf. Algorithm aversion, however, might prevent consumers from using automated commerce and thereby stymie this promising technology. This research project applies principal-agent theory, a theory mostly used in B2B contexts, to the consumer behavior realm to analyze consumers’ willingness to accept service failure in automated retailing schemes. While consumers are less forgiving towards agents in situations with specific expectations (predefined automation), they are more forgiving and actually accepting of service failures in situations with vague expectations (surprise automation). This project, thus, seeks to identify ways for firms to increase consumers’ acceptance of service failures in agency situations and increase lifetime value in automated commerce.