Ethical Consumption and Social Context: Experimental Evidence from Germany and the United States

This research examines the role of social context in ethical consumption, specifically, the extent to which anonymity and social control influence individuals' decisions to purchase organic and Fair Trade coffee. Our research design overcomes biases of prior research by combining framing and discrete choice experiments in a survey. We systematically vary coffee growing method (organic or not), import status (Fair Trade or not), flavor, and price across four social contexts that vary in degree of anonymity and normative social control. The social contexts are buying coffee online, in a large grocery store, in a small neighborhood shop, and for a meeting of a human rights group. Subjects comprise 1,103 German and American undergraduate students. We find that social context indeed influences subjects' ethical consumer decisions, especially in situations with low anonymity and high social control. In addition, gender, coffee buying, and subjective social norms trigger heterogeneity regarding stated ethical consumption and the effects of social context. These results suggest previous research has underestimated the relevance of social context for ethical consumption and overestimated altruistic motives of ethical consumers. Our study demonstrates the great potential of discrete choice experiments for the study of social action and decision making processes in sociology.

Land acquisition, investment, and development in the Lao coffee sector: Successes and failures

Despite the increasing acknowledgment of scholars and practitioners that many large-scale agricultural land acquisitions in developing countries fail or never materialize, empirical evidence about how and why they fail to date is still scarce. Too often, land deals are portrayed as straightforward investments and their success is taken for granted. Looking at the coffee sector in Laos, the authors of this article explore dimensions of the land grab debate that have not yet been sufficiently examined. Coffee concessionaires in southern Laos often fail to use all of the land granted them and fail to produce high yields on the land they do use. Thus, the authors challenge the often-assumed superiority and effectiveness of large-scale versus small-scale production, specifically the argument that they modernize agricultural production and optimize land use. They argue that examining failed investments is as important as studying successful ones for understanding the implications of the land grabbing phenomenon for social, economic, and environmental outcomes. Knowledge about the scale of “failed land deals” provides important motivation for national governments to close the gap between intentions and actual outcomes. This article engages with the current debate on quality of investment and challenges the approach of employing land concessions as a vehicle for economic development in the Lao coffee sector and in other sectors and countries.

The influence of formal and informal sales controls on customer-directed selling behaviors and sales unit effectiveness

Adaptive selling (AS) and customer-oriented selling (COS) constitute two key customer-directed selling behaviors for the success of the modern sales force. However, knowledge regarding the organizational factors that can induce salespeople to engage in those behaviors is strikingly limited. Against this background, we develop a comprehensive model that delineates the influences of formal and informal sales controls on AS and COS and, through them, on sales unit effectiveness. Based on a sample of sales managers in a major European Union country, we present new evidence that (a) formal and informal sales controls exert differential impact on salespeople's AS and COS behaviors; (b) AS directly and positively influences sales unit effectiveness; (c) COS affects sales unit effectiveness only indirectly, i.e. by fostering AS; and (d) outcome and cultural controls directly improve sales unit effectiveness. We conclude with a discussion of our findings for academics and practitioners.

Dangers of ‘Facebook Login’ for Mobile Apps: Is There a Price Tag for Social Information?

Social networks offer horizontal integration for any mobile platform providing app users with a convenient single sign-on point. Nonetheless, there are growing privacy concerns regarding its use. These vulnerabilities trigger alarm among app developers who fight for their user base: While they are happy to act on users’ information collected via social networks, they are not always willing to sacrifice their adoption rate for this goal. So far, understanding of this trade-off has remained ambiguous. To fill this gap, we employ a discrete choice experiment to explore the role of Facebook Login and investigate the impact of accompanying requests for different information items / actions in the mobile app adoption process. We quantify users’ concerns regarding these items in monetary terms. Beyond hands-on insights for providers, our study contributes to the theoretical discourse on the value of privacy in the growing world of Social Media and mobile web.

Forecasting Intraday Stock Price Trends with Text Mining Techniques

In this paper, we describe NewsCATS (news categorization and trading system), a system implemented to predict stock price trends for the time immediately after the publication of press releases. NewsCATS consists mainly of three components. The first component retrieves relevant information from press releases through the application of text preprocessing techniques. The second component sorts the press releases into predefined categories. Finally, appropriate trading strategies are derived by the third component by means of the earlier categorization. The findings indicate that a categorization of press releases is able to provide additional information that can be used to forecast stock price trends, but that an adequate trading strategy is essential for the results of the categorization to be fully exploited.

Partitioning the Choice Task Makes Starbucks Coffee Taste Better

Consumers are often less satisfied with a product chosen from a large assortment than a limited one. Experienced choice difficulty presumably causes this as consumers have to engage in a great number of individual comparisons. In two studies we tested whether partitioning the choice task so that consumers decided sequentially on each individual attribute may provide a solution. In a Starbucks coffee house, consumers who chose from the menu rated the coffee as less tasty when chosen from a large rather than a small assortment. However, when the consumers chose it by sequentially deciding about one attribute at a time, the effect reversed. In a tailored-suit customization, consumers who chose multiple attributes at a time were less satisfied with their suit, compared to those who chose one attribute at a time. Sequential attribute-based processing proves to be an effective strategy to reap the benefits of a large assortment.